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<a href="gpu_2dense_8hpp.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a id="l00001" name="l00001"></a><span class="lineno">    1</span><span class="comment">/*!</span></div>
<div class="line"><a id="l00002" name="l00002"></a><span class="lineno">    2</span><span class="comment"> * \brief       Implements the dense matrix class for the gpu</span></div>
<div class="line"><a id="l00003" name="l00003"></a><span class="lineno">    3</span><span class="comment"> * </span></div>
<div class="line"><a id="l00004" name="l00004"></a><span class="lineno">    4</span><span class="comment"> * \author      O. Krause</span></div>
<div class="line"><a id="l00005" name="l00005"></a><span class="lineno">    5</span><span class="comment"> * \date        2016</span></div>
<div class="line"><a id="l00006" name="l00006"></a><span class="lineno">    6</span><span class="comment"> *</span></div>
<div class="line"><a id="l00007" name="l00007"></a><span class="lineno">    7</span><span class="comment"> *</span></div>
<div class="line"><a id="l00008" name="l00008"></a><span class="lineno">    8</span><span class="comment"> * \par Copyright 1995-2015 Shark Development Team</span></div>
<div class="line"><a id="l00009" name="l00009"></a><span class="lineno">    9</span><span class="comment"> * </span></div>
<div class="line"><a id="l00010" name="l00010"></a><span class="lineno">   10</span><span class="comment"> * &lt;BR&gt;&lt;HR&gt;</span></div>
<div class="line"><a id="l00011" name="l00011"></a><span class="lineno">   11</span><span class="comment"> * This file is part of Shark.</span></div>
<div class="line"><a id="l00012" name="l00012"></a><span class="lineno">   12</span><span class="comment"> * &lt;http://image.diku.dk/shark/&gt;</span></div>
<div class="line"><a id="l00013" name="l00013"></a><span class="lineno">   13</span><span class="comment"> * </span></div>
<div class="line"><a id="l00014" name="l00014"></a><span class="lineno">   14</span><span class="comment"> * Shark is free software: you can redistribute it and/or modify</span></div>
<div class="line"><a id="l00015" name="l00015"></a><span class="lineno">   15</span><span class="comment"> * it under the terms of the GNU Lesser General Public License as published </span></div>
<div class="line"><a id="l00016" name="l00016"></a><span class="lineno">   16</span><span class="comment"> * by the Free Software Foundation, either version 3 of the License, or</span></div>
<div class="line"><a id="l00017" name="l00017"></a><span class="lineno">   17</span><span class="comment"> * (at your option) any later version.</span></div>
<div class="line"><a id="l00018" name="l00018"></a><span class="lineno">   18</span><span class="comment"> * </span></div>
<div class="line"><a id="l00019" name="l00019"></a><span class="lineno">   19</span><span class="comment"> * Shark is distributed in the hope that it will be useful,</span></div>
<div class="line"><a id="l00020" name="l00020"></a><span class="lineno">   20</span><span class="comment"> * but WITHOUT ANY WARRANTY; without even the implied warranty of</span></div>
<div class="line"><a id="l00021" name="l00021"></a><span class="lineno">   21</span><span class="comment"> * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the</span></div>
<div class="line"><a id="l00022" name="l00022"></a><span class="lineno">   22</span><span class="comment"> * GNU Lesser General Public License for more details.</span></div>
<div class="line"><a id="l00023" name="l00023"></a><span class="lineno">   23</span><span class="comment"> * </span></div>
<div class="line"><a id="l00024" name="l00024"></a><span class="lineno">   24</span><span class="comment"> * You should have received a copy of the GNU Lesser General Public License</span></div>
<div class="line"><a id="l00025" name="l00025"></a><span class="lineno">   25</span><span class="comment"> * along with Shark.  If not, see &lt;http://www.gnu.org/licenses/&gt;.</span></div>
<div class="line"><a id="l00026" name="l00026"></a><span class="lineno">   26</span><span class="comment"> *</span></div>
<div class="line"><a id="l00027" name="l00027"></a><span class="lineno">   27</span><span class="comment"> */</span></div>
<div class="line"><a id="l00028" name="l00028"></a><span class="lineno">   28</span><span class="preprocessor">#ifndef REMORA_GPU_DENSE_HPP</span></div>
<div class="line"><a id="l00029" name="l00029"></a><span class="lineno">   29</span><span class="preprocessor">#define REMORA_GPU_DENSE_HPP</span></div>
<div class="line"><a id="l00030" name="l00030"></a><span class="lineno">   30</span> </div>
<div class="line"><a id="l00031" name="l00031"></a><span class="lineno">   31</span><span class="preprocessor">#include &quot;../detail/traits.hpp&quot;</span></div>
<div class="line"><a id="l00032" name="l00032"></a><span class="lineno">   32</span><span class="preprocessor">#include &quot;../assignment.hpp&quot;</span></div>
<div class="line"><a id="l00033" name="l00033"></a><span class="lineno">   33</span><span class="preprocessor">#include &lt;boost/compute/container/vector.hpp&gt;</span></div>
<div class="line"><a id="l00034" name="l00034"></a><span class="lineno">   34</span><span class="preprocessor">#include &lt;boost/compute/iterator/strided_iterator.hpp&gt;</span></div>
<div class="line"><a id="l00035" name="l00035"></a><span class="lineno">   35</span><span class="preprocessor">#include &lt;boost/compute/algorithm/fill.hpp&gt;</span></div>
<div class="line"><a id="l00036" name="l00036"></a><span class="lineno">   36</span><span class="keyword">namespace </span>remora{</div>
<div class="line"><a id="l00037" name="l00037"></a><span class="lineno">   37</span>    </div>
<div class="line"><a id="l00038" name="l00038"></a><span class="lineno">   38</span>    </div>
<div class="line"><a id="l00039" name="l00039"></a><span class="lineno">   39</span><span class="keyword">template</span>&lt;<span class="keyword">class</span> T, <span class="keyword">class</span> Tag&gt;</div>
<div class="line"><a id="l00040" name="l00040"></a><span class="lineno">   40</span><span class="keyword">class </span>dense_vector_adaptor&lt;T, Tag, gpu_tag&gt;: <span class="keyword">public</span> vector_expression&lt;dense_vector_adaptor&lt;T, Tag, gpu_tag&gt;, gpu_tag &gt; {</div>
<div class="line"><a id="l00041" name="l00041"></a><span class="lineno">   41</span><span class="keyword">public</span>:</div>
<div class="line"><a id="l00042" name="l00042"></a><span class="lineno">   42</span>    <span class="keyword">typedef</span> std::size_t size_type;</div>
<div class="line"><a id="l00043" name="l00043"></a><span class="lineno">   43</span>    <span class="keyword">typedef</span> <span class="keyword">typename</span> std::remove_const&lt;T&gt;::type value_type;</div>
<div class="line"><a id="l00044" name="l00044"></a><span class="lineno">   44</span>    <span class="keyword">typedef</span> value_type <span class="keyword">const</span>&amp; const_reference;</div>
<div class="line"><a id="l00045" name="l00045"></a><span class="lineno">   45</span>    <span class="keyword">typedef</span> T&amp;  reference;</div>
<div class="line"><a id="l00046" name="l00046"></a><span class="lineno">   46</span> </div>
<div class="line"><a id="l00047" name="l00047"></a><span class="lineno">   47</span>    <span class="keyword">typedef</span> dense_vector_adaptor&lt;T const, Tag, gpu_tag&gt; const_closure_type;</div>
<div class="line"><a id="l00048" name="l00048"></a><span class="lineno">   48</span>    <span class="keyword">typedef</span> dense_vector_adaptor closure_type;</div>
<div class="line"><a id="l00049" name="l00049"></a><span class="lineno">   49</span>    <span class="keyword">typedef</span> gpu::dense_vector_storage&lt;T, Tag&gt; storage_type;</div>
<div class="line"><a id="l00050" name="l00050"></a><span class="lineno">   50</span>    <span class="keyword">typedef</span> gpu::dense_vector_storage&lt;value_type const, Tag&gt; const_storage_type;</div>
<div class="line"><a id="l00051" name="l00051"></a><span class="lineno">   51</span>    <span class="keyword">typedef</span> elementwise&lt;dense_tag&gt; evaluation_category;</div>
<div class="line"><a id="l00052" name="l00052"></a><span class="lineno">   52</span> </div>
<div class="line"><a id="l00053" name="l00053"></a><span class="lineno">   53</span>    <span class="comment">// Construction and destruction</span></div>
<div class="line"><a id="l00054" name="l00054"></a><span class="lineno">   54</span><span class="comment"></span> </div>
<div class="line"><a id="l00055" name="l00055"></a><span class="lineno">   55</span><span class="comment">    /// \brief Copy-constructor</span></div>
<div class="line"><a id="l00056" name="l00056"></a><span class="lineno">   56</span><span class="comment">    /// \param v is the proxy to be copied</span></div>
<div class="line"><a id="l00057" name="l00057"></a><span class="lineno">   57</span><span class="comment"></span>    <span class="keyword">template</span>&lt;<span class="keyword">class</span> U, <span class="keyword">class</span> Tag2&gt;</div>
<div class="line"><a id="l00058" name="l00058"></a><span class="lineno">   58</span>    dense_vector_adaptor(dense_vector_adaptor&lt;U, Tag2, gpu_tag&gt; <span class="keyword">const</span>&amp; v)</div>
<div class="line"><a id="l00059" name="l00059"></a><span class="lineno">   59</span>    : m_storage(v.raw_storage())</div>
<div class="line"><a id="l00060" name="l00060"></a><span class="lineno">   60</span>    , m_queue(&amp;v.queue())</div>
<div class="line"><a id="l00061" name="l00061"></a><span class="lineno">   61</span>    , m_size(v.size()){<span class="keyword">static_assert</span>(std::is_convertible&lt;Tag2,Tag&gt;::value, <span class="stringliteral">&quot;Can not convert storage type of argument to the given Tag&quot;</span>);}</div>
<div class="line"><a id="l00062" name="l00062"></a><span class="lineno">   62</span>    <span class="comment"></span></div>
<div class="line"><a id="l00063" name="l00063"></a><span class="lineno">   63</span><span class="comment">    /// \brief Constructor of a vector proxy from a block of memory</span></div>
<div class="line"><a id="l00064" name="l00064"></a><span class="lineno">   64</span><span class="comment">    /// \param storage the block of memory used</span></div>
<div class="line"><a id="l00065" name="l00065"></a><span class="lineno">   65</span><span class="comment">    /// \param size number of elements</span></div>
<div class="line"><a id="l00066" name="l00066"></a><span class="lineno">   66</span><span class="comment"></span>    dense_vector_adaptor(</div>
<div class="line"><a id="l00067" name="l00067"></a><span class="lineno">   67</span>        storage_type storage, </div>
<div class="line"><a id="l00068" name="l00068"></a><span class="lineno">   68</span>        boost::compute::command_queue&amp; queue,</div>
<div class="line"><a id="l00069" name="l00069"></a><span class="lineno">   69</span>        size_type size</div>
<div class="line"><a id="l00070" name="l00070"></a><span class="lineno">   70</span>    ):m_storage(storage)</div>
<div class="line"><a id="l00071" name="l00071"></a><span class="lineno">   71</span>    , m_queue(&amp;queue)</div>
<div class="line"><a id="l00072" name="l00072"></a><span class="lineno">   72</span>    , m_size(size){}</div>
<div class="line"><a id="l00073" name="l00073"></a><span class="lineno">   73</span>    </div>
<div class="line"><a id="l00074" name="l00074"></a><span class="lineno">   74</span>    dense_vector_adaptor(vector&lt;value_type, gpu_tag&gt; <span class="keyword">const</span>&amp; v)</div>
<div class="line"><a id="l00075" name="l00075"></a><span class="lineno">   75</span>    : m_storage(v().raw_storage())</div>
<div class="line"><a id="l00076" name="l00076"></a><span class="lineno">   76</span>    , m_queue(&amp;v().queue())</div>
<div class="line"><a id="l00077" name="l00077"></a><span class="lineno">   77</span>    , m_size(v().size()){}</div>
<div class="line"><a id="l00078" name="l00078"></a><span class="lineno">   78</span>    </div>
<div class="line"><a id="l00079" name="l00079"></a><span class="lineno">   79</span>    dense_vector_adaptor(vector&lt;value_type, gpu_tag&gt;&amp; v)</div>
<div class="line"><a id="l00080" name="l00080"></a><span class="lineno">   80</span>    : m_storage(v().raw_storage())</div>
<div class="line"><a id="l00081" name="l00081"></a><span class="lineno">   81</span>    , m_queue(&amp;v().queue())</div>
<div class="line"><a id="l00082" name="l00082"></a><span class="lineno">   82</span>    , m_size(v().size()){}</div>
<div class="line"><a id="l00083" name="l00083"></a><span class="lineno">   83</span>    </div>
<div class="line"><a id="l00084" name="l00084"></a><span class="lineno">   84</span>    <span class="comment">// -------------------</span></div>
<div class="line"><a id="l00085" name="l00085"></a><span class="lineno">   85</span>    <span class="comment">// Assignment operators</span></div>
<div class="line"><a id="l00086" name="l00086"></a><span class="lineno">   86</span>    <span class="comment">// -------------------</span></div>
<div class="line"><a id="l00087" name="l00087"></a><span class="lineno">   87</span>    </div>
<div class="line"><a id="l00088" name="l00088"></a><span class="lineno">   88</span>    dense_vector_adaptor&amp; operator = (dense_vector_adaptor <span class="keyword">const</span>&amp; e) {</div>
<div class="line"><a id="l00089" name="l00089"></a><span class="lineno">   89</span>        REMORA_SIZE_CHECK(size() == e().size());</div>
<div class="line"><a id="l00090" name="l00090"></a><span class="lineno">   90</span>        <span class="keywordflow">return</span> assign(*<span class="keyword">this</span>, <span class="keyword">typename</span> vector_temporary&lt;dense_vector_adaptor&gt;::type(e));</div>
<div class="line"><a id="l00091" name="l00091"></a><span class="lineno">   91</span>    }</div>
<div class="line"><a id="l00092" name="l00092"></a><span class="lineno">   92</span>    <span class="keyword">template</span>&lt;<span class="keyword">class</span> E&gt;</div>
<div class="line"><a id="l00093" name="l00093"></a><span class="lineno">   93</span>    dense_vector_adaptor&amp; operator = (vector_expression&lt;E, gpu_tag&gt; <span class="keyword">const</span>&amp; e) {</div>
<div class="line"><a id="l00094" name="l00094"></a><span class="lineno">   94</span>        REMORA_SIZE_CHECK(size() == e().size());</div>
<div class="line"><a id="l00095" name="l00095"></a><span class="lineno">   95</span>        <span class="keywordflow">return</span> assign(*<span class="keyword">this</span>, <span class="keyword">typename</span> vector_temporary&lt;dense_vector_adaptor&gt;::type(e));</div>
<div class="line"><a id="l00096" name="l00096"></a><span class="lineno">   96</span>    }</div>
<div class="line"><a id="l00097" name="l00097"></a><span class="lineno">   97</span>    <span class="comment"></span></div>
<div class="line"><a id="l00098" name="l00098"></a><span class="lineno">   98</span><span class="comment">    /// \brief Return the size of the vector.</span></div>
<div class="line"><a id="l00099" name="l00099"></a><span class="lineno">   99</span><span class="comment"></span>    size_type size()<span class="keyword"> const </span>{</div>
<div class="line"><a id="l00100" name="l00100"></a><span class="lineno">  100</span>        <span class="keywordflow">return</span> m_size;</div>
<div class="line"><a id="l00101" name="l00101"></a><span class="lineno">  101</span>    }</div>
<div class="line"><a id="l00102" name="l00102"></a><span class="lineno">  102</span>    <span class="comment"></span></div>
<div class="line"><a id="l00103" name="l00103"></a><span class="lineno">  103</span><span class="comment">    ///\brief Returns the underlying storage_type structure for low level access</span></div>
<div class="line"><a id="l00104" name="l00104"></a><span class="lineno">  104</span><span class="comment"></span>    storage_type raw_storage()<span class="keyword"> const</span>{</div>
<div class="line"><a id="l00105" name="l00105"></a><span class="lineno">  105</span>        <span class="keywordflow">return</span> m_storage;</div>
<div class="line"><a id="l00106" name="l00106"></a><span class="lineno">  106</span>    }</div>
<div class="line"><a id="l00107" name="l00107"></a><span class="lineno">  107</span>    </div>
<div class="line"><a id="l00108" name="l00108"></a><span class="lineno">  108</span>    boost::compute::command_queue&amp; queue()<span class="keyword"> const</span>{</div>
<div class="line"><a id="l00109" name="l00109"></a><span class="lineno">  109</span>        <span class="keywordflow">return</span> *m_queue;</div>
<div class="line"><a id="l00110" name="l00110"></a><span class="lineno">  110</span>    }</div>
<div class="line"><a id="l00111" name="l00111"></a><span class="lineno">  111</span>    </div>
<div class="line"><a id="l00112" name="l00112"></a><span class="lineno">  112</span>    <span class="keywordtype">void</span> clear(){</div>
<div class="line"><a id="l00113" name="l00113"></a><span class="lineno">  113</span>        gpu::detail::meta_kernel k(<span class="stringliteral">&quot;vector_proxy_clear&quot;</span>);</div>
<div class="line"><a id="l00114" name="l00114"></a><span class="lineno">  114</span>        <span class="keyword">auto</span> v = k.register_args(to_functor(*<span class="keyword">this</span>));</div>
<div class="line"><a id="l00115" name="l00115"></a><span class="lineno">  115</span>    </div>
<div class="line"><a id="l00116" name="l00116"></a><span class="lineno">  116</span>        <span class="comment">//create source</span></div>
<div class="line"><a id="l00117" name="l00117"></a><span class="lineno">  117</span>        k&lt;&lt;v(k.get_global_id(0))&lt;&lt;<span class="stringliteral">&quot; = 0;&quot;</span>;</div>
<div class="line"><a id="l00118" name="l00118"></a><span class="lineno">  118</span>        boost::compute::kernel kernel = k.compile(queue().get_context());</div>
<div class="line"><a id="l00119" name="l00119"></a><span class="lineno">  119</span>        <span class="comment">//enqueue kernel</span></div>
<div class="line"><a id="l00120" name="l00120"></a><span class="lineno">  120</span>        std::size_t global_work_size[1] = {size()};</div>
<div class="line"><a id="l00121" name="l00121"></a><span class="lineno">  121</span>        queue().enqueue_nd_range_kernel(kernel, 1,<span class="keyword">nullptr</span>, global_work_size, <span class="keyword">nullptr</span>);</div>
<div class="line"><a id="l00122" name="l00122"></a><span class="lineno">  122</span>    }</div>
<div class="line"><a id="l00123" name="l00123"></a><span class="lineno">  123</span>    </div>
<div class="line"><a id="l00124" name="l00124"></a><span class="lineno">  124</span>    <span class="keyword">typedef</span> no_iterator iterator;</div>
<div class="line"><a id="l00125" name="l00125"></a><span class="lineno">  125</span>    <span class="keyword">typedef</span> no_iterator const_iterator;</div>
<div class="line"><a id="l00126" name="l00126"></a><span class="lineno">  126</span>    </div>
<div class="line"><a id="l00127" name="l00127"></a><span class="lineno">  127</span><span class="keyword">private</span>:</div>
<div class="line"><a id="l00128" name="l00128"></a><span class="lineno">  128</span>    <span class="keyword">template</span>&lt;<span class="keyword">class</span>,<span class="keyword">class</span>,<span class="keyword">class</span>&gt; <span class="keyword">friend</span> <span class="keyword">class </span>dense_vector_adaptor;</div>
<div class="line"><a id="l00129" name="l00129"></a><span class="lineno">  129</span>    dense_vector_adaptor(vector&lt;value_type, gpu_tag&gt; &amp;&amp; v);<span class="comment">//no construction from temporary vector</span></div>
<div class="line"><a id="l00130" name="l00130"></a><span class="lineno">  130</span> </div>
<div class="line"><a id="l00131" name="l00131"></a><span class="lineno">  131</span>    storage_type m_storage;</div>
<div class="line"><a id="l00132" name="l00132"></a><span class="lineno">  132</span>    boost::compute::command_queue* m_queue;</div>
<div class="line"><a id="l00133" name="l00133"></a><span class="lineno">  133</span>    size_type m_size;</div>
<div class="line"><a id="l00134" name="l00134"></a><span class="lineno">  134</span>};</div>
<div class="line"><a id="l00135" name="l00135"></a><span class="lineno">  135</span>    </div>
<div class="line"><a id="l00136" name="l00136"></a><span class="lineno">  136</span><span class="keyword">template</span>&lt;<span class="keyword">class</span> T,<span class="keyword">class</span> Orientation, <span class="keyword">class</span> Tag&gt;</div>
<div class="line"><a id="l00137" name="l00137"></a><span class="lineno">  137</span><span class="keyword">class </span>dense_matrix_adaptor&lt;T, Orientation, Tag, gpu_tag&gt;: <span class="keyword">public</span> matrix_expression&lt;dense_matrix_adaptor&lt;T,Orientation, Tag, gpu_tag&gt;, gpu_tag &gt; {</div>
<div class="line"><a id="l00138" name="l00138"></a><span class="lineno">  138</span><span class="keyword">public</span>:</div>
<div class="line"><a id="l00139" name="l00139"></a><span class="lineno">  139</span>    <span class="keyword">typedef</span> std::size_t size_type;</div>
<div class="line"><a id="l00140" name="l00140"></a><span class="lineno">  140</span>    <span class="keyword">typedef</span> <span class="keyword">typename</span> std::remove_const&lt;T&gt;::type value_type;</div>
<div class="line"><a id="l00141" name="l00141"></a><span class="lineno">  141</span>    <span class="keyword">typedef</span> value_type <span class="keyword">const</span>&amp; const_reference;</div>
<div class="line"><a id="l00142" name="l00142"></a><span class="lineno">  142</span>    <span class="keyword">typedef</span> T&amp; reference;</div>
<div class="line"><a id="l00143" name="l00143"></a><span class="lineno">  143</span> </div>
<div class="line"><a id="l00144" name="l00144"></a><span class="lineno">  144</span>    <span class="keyword">typedef</span> dense_matrix_adaptor closure_type;</div>
<div class="line"><a id="l00145" name="l00145"></a><span class="lineno">  145</span>    <span class="keyword">typedef</span> dense_matrix_adaptor&lt;value_type const, Orientation, Tag, gpu_tag&gt; const_closure_type;</div>
<div class="line"><a id="l00146" name="l00146"></a><span class="lineno">  146</span>    <span class="keyword">typedef</span> gpu::dense_matrix_storage&lt;T, Tag&gt; storage_type;</div>
<div class="line"><a id="l00147" name="l00147"></a><span class="lineno">  147</span>    <span class="keyword">typedef</span> gpu::dense_matrix_storage&lt;value_type const, Tag&gt; const_storage_type;</div>
<div class="line"><a id="l00148" name="l00148"></a><span class="lineno">  148</span>        <span class="keyword">typedef</span> Orientation orientation;</div>
<div class="line"><a id="l00149" name="l00149"></a><span class="lineno">  149</span>    <span class="keyword">typedef</span> elementwise&lt;dense_tag&gt; evaluation_category;</div>
<div class="line"><a id="l00150" name="l00150"></a><span class="lineno">  150</span> </div>
<div class="line"><a id="l00151" name="l00151"></a><span class="lineno">  151</span>    <span class="comment">// Construction and destruction</span></div>
<div class="line"><a id="l00152" name="l00152"></a><span class="lineno">  152</span>    <span class="keyword">template</span>&lt;<span class="keyword">class</span> U, <span class="keyword">class</span> Tag2&gt;</div>
<div class="line"><a id="l00153" name="l00153"></a><span class="lineno">  153</span>    dense_matrix_adaptor(dense_matrix_adaptor&lt;U, Orientation, Tag2, gpu_tag&gt; <span class="keyword">const</span>&amp; expression)</div>
<div class="line"><a id="l00154" name="l00154"></a><span class="lineno">  154</span>    : m_storage(expression.raw_storage())</div>
<div class="line"><a id="l00155" name="l00155"></a><span class="lineno">  155</span>    , m_queue(&amp;expression.queue())</div>
<div class="line"><a id="l00156" name="l00156"></a><span class="lineno">  156</span>    , m_size1(expression.size1())</div>
<div class="line"><a id="l00157" name="l00157"></a><span class="lineno">  157</span>    , m_size2(expression.size2())</div>
<div class="line"><a id="l00158" name="l00158"></a><span class="lineno">  158</span>    {<span class="keyword">static_assert</span>(std::is_convertible&lt;Tag2,Tag&gt;::value, <span class="stringliteral">&quot;Can not convert storage type of argument to the given Tag&quot;</span>);}</div>
<div class="line"><a id="l00159" name="l00159"></a><span class="lineno">  159</span>        <span class="comment"></span></div>
<div class="line"><a id="l00160" name="l00160"></a><span class="lineno">  160</span><span class="comment">    /// \brief Constructor of a matrix proxy from a block of memory</span></div>
<div class="line"><a id="l00161" name="l00161"></a><span class="lineno">  161</span><span class="comment">    /// \param storage the block of memory used</span></div>
<div class="line"><a id="l00162" name="l00162"></a><span class="lineno">  162</span><span class="comment">    /// \param size1 number of rows</span></div>
<div class="line"><a id="l00163" name="l00163"></a><span class="lineno">  163</span><span class="comment">    /// \param size2 number of columns</span></div>
<div class="line"><a id="l00164" name="l00164"></a><span class="lineno">  164</span><span class="comment"></span>    dense_matrix_adaptor(</div>
<div class="line"><a id="l00165" name="l00165"></a><span class="lineno">  165</span>        storage_type storage, </div>
<div class="line"><a id="l00166" name="l00166"></a><span class="lineno">  166</span>        boost::compute::command_queue&amp; queue,</div>
<div class="line"><a id="l00167" name="l00167"></a><span class="lineno">  167</span>        size_type size1, size_type size2</div>
<div class="line"><a id="l00168" name="l00168"></a><span class="lineno">  168</span>    ):m_storage(storage)</div>
<div class="line"><a id="l00169" name="l00169"></a><span class="lineno">  169</span>    , m_queue(&amp;queue)</div>
<div class="line"><a id="l00170" name="l00170"></a><span class="lineno">  170</span>    , m_size1(size1)</div>
<div class="line"><a id="l00171" name="l00171"></a><span class="lineno">  171</span>    , m_size2(size2){}</div>
<div class="line"><a id="l00172" name="l00172"></a><span class="lineno">  172</span>    </div>
<div class="line"><a id="l00173" name="l00173"></a><span class="lineno">  173</span>    dense_matrix_adaptor(matrix&lt;value_type, Orientation, gpu_tag&gt; <span class="keyword">const</span>&amp; m )</div>
<div class="line"><a id="l00174" name="l00174"></a><span class="lineno">  174</span>    : m_storage(m().raw_storage())</div>
<div class="line"><a id="l00175" name="l00175"></a><span class="lineno">  175</span>    , m_queue(&amp;m().queue())</div>
<div class="line"><a id="l00176" name="l00176"></a><span class="lineno">  176</span>    , m_size1(m().size1())</div>
<div class="line"><a id="l00177" name="l00177"></a><span class="lineno">  177</span>    , m_size2(m().size2()){}</div>
<div class="line"><a id="l00178" name="l00178"></a><span class="lineno">  178</span>    </div>
<div class="line"><a id="l00179" name="l00179"></a><span class="lineno">  179</span>    dense_matrix_adaptor(matrix&lt;value_type, Orientation, gpu_tag&gt;&amp; m )</div>
<div class="line"><a id="l00180" name="l00180"></a><span class="lineno">  180</span>    : m_storage(m().raw_storage())</div>
<div class="line"><a id="l00181" name="l00181"></a><span class="lineno">  181</span>    , m_queue(&amp;m().queue())</div>
<div class="line"><a id="l00182" name="l00182"></a><span class="lineno">  182</span>    , m_size1(m().size1())</div>
<div class="line"><a id="l00183" name="l00183"></a><span class="lineno">  183</span>    , m_size2(m().size2()){}</div>
<div class="line"><a id="l00184" name="l00184"></a><span class="lineno">  184</span>    </div>
<div class="line"><a id="l00185" name="l00185"></a><span class="lineno">  185</span>    <span class="comment">// -------------------</span></div>
<div class="line"><a id="l00186" name="l00186"></a><span class="lineno">  186</span>    <span class="comment">// Assignment operators</span></div>
<div class="line"><a id="l00187" name="l00187"></a><span class="lineno">  187</span>    <span class="comment">// -------------------</span></div>
<div class="line"><a id="l00188" name="l00188"></a><span class="lineno">  188</span>    </div>
<div class="line"><a id="l00189" name="l00189"></a><span class="lineno">  189</span>    dense_matrix_adaptor&amp; operator = (dense_matrix_adaptor <span class="keyword">const</span>&amp; e) {</div>
<div class="line"><a id="l00190" name="l00190"></a><span class="lineno">  190</span>        REMORA_SIZE_CHECK(size1() == e().size1());</div>
<div class="line"><a id="l00191" name="l00191"></a><span class="lineno">  191</span>        REMORA_SIZE_CHECK(size2() == e().size2());</div>
<div class="line"><a id="l00192" name="l00192"></a><span class="lineno">  192</span>        <span class="keywordflow">return</span> assign(*<span class="keyword">this</span>, <span class="keyword">typename</span> matrix_temporary&lt;dense_matrix_adaptor&gt;::type(e));</div>
<div class="line"><a id="l00193" name="l00193"></a><span class="lineno">  193</span>    }</div>
<div class="line"><a id="l00194" name="l00194"></a><span class="lineno">  194</span>    <span class="keyword">template</span>&lt;<span class="keyword">class</span> E&gt;</div>
<div class="line"><a id="l00195" name="l00195"></a><span class="lineno">  195</span>    dense_matrix_adaptor&amp; operator = (matrix_expression&lt;E, gpu_tag&gt; <span class="keyword">const</span>&amp; e) {</div>
<div class="line"><a id="l00196" name="l00196"></a><span class="lineno">  196</span>        REMORA_SIZE_CHECK(size1() == e().size1());</div>
<div class="line"><a id="l00197" name="l00197"></a><span class="lineno">  197</span>        REMORA_SIZE_CHECK(size2() == e().size2());</div>
<div class="line"><a id="l00198" name="l00198"></a><span class="lineno">  198</span>        <span class="keywordflow">return</span> assign(*<span class="keyword">this</span>, <span class="keyword">typename</span> matrix_temporary&lt;dense_matrix_adaptor&gt;::type(e));</div>
<div class="line"><a id="l00199" name="l00199"></a><span class="lineno">  199</span>    }</div>
<div class="line"><a id="l00200" name="l00200"></a><span class="lineno">  200</span>    <span class="keyword">template</span>&lt;<span class="keyword">class</span> E&gt;</div>
<div class="line"><a id="l00201" name="l00201"></a><span class="lineno">  201</span>    dense_matrix_adaptor&amp; operator = (vector_set_expression&lt;E, gpu_tag&gt; <span class="keyword">const</span>&amp; e) {</div>
<div class="line"><a id="l00202" name="l00202"></a><span class="lineno">  202</span>        REMORA_SIZE_CHECK(size1() == <span class="keyword">typename</span> E::point_orientation::index_M(e().size(), e().point_size()));</div>
<div class="line"><a id="l00203" name="l00203"></a><span class="lineno">  203</span>        REMORA_SIZE_CHECK(size2() == <span class="keyword">typename</span> E::point_orientation::index_M(e().size(), e().point_size()));</div>
<div class="line"><a id="l00204" name="l00204"></a><span class="lineno">  204</span>        <span class="keywordflow">return</span> assign(*<span class="keyword">this</span>, <span class="keyword">typename</span> matrix_temporary&lt;dense_matrix_adaptor&gt;::type(e));</div>
<div class="line"><a id="l00205" name="l00205"></a><span class="lineno">  205</span>    }</div>
<div class="line"><a id="l00206" name="l00206"></a><span class="lineno">  206</span> </div>
<div class="line"><a id="l00207" name="l00207"></a><span class="lineno">  207</span>    <span class="comment">// ---------</span></div>
<div class="line"><a id="l00208" name="l00208"></a><span class="lineno">  208</span>    <span class="comment">// Storage interface</span></div>
<div class="line"><a id="l00209" name="l00209"></a><span class="lineno">  209</span>    <span class="comment">// ---------</span></div>
<div class="line"><a id="l00210" name="l00210"></a><span class="lineno">  210</span>    <span class="comment"></span></div>
<div class="line"><a id="l00211" name="l00211"></a><span class="lineno">  211</span><span class="comment">    ///\brief Returns the number of rows of the matrix.</span></div>
<div class="line"><a id="l00212" name="l00212"></a><span class="lineno">  212</span><span class="comment"></span>    size_type size1()<span class="keyword"> const </span>{</div>
<div class="line"><a id="l00213" name="l00213"></a><span class="lineno">  213</span>        <span class="keywordflow">return</span> m_size1;</div>
<div class="line"><a id="l00214" name="l00214"></a><span class="lineno">  214</span>    }<span class="comment"></span></div>
<div class="line"><a id="l00215" name="l00215"></a><span class="lineno">  215</span><span class="comment">    ///\brief Returns the number of columns of the matrix.</span></div>
<div class="line"><a id="l00216" name="l00216"></a><span class="lineno">  216</span><span class="comment"></span>    size_type size2()<span class="keyword"> const </span>{</div>
<div class="line"><a id="l00217" name="l00217"></a><span class="lineno">  217</span>        <span class="keywordflow">return</span> m_size2;</div>
<div class="line"><a id="l00218" name="l00218"></a><span class="lineno">  218</span>    }</div>
<div class="line"><a id="l00219" name="l00219"></a><span class="lineno">  219</span>    </div>
<div class="line"><a id="l00220" name="l00220"></a><span class="lineno">  220</span>    boost::compute::command_queue&amp; queue()<span class="keyword"> const</span>{</div>
<div class="line"><a id="l00221" name="l00221"></a><span class="lineno">  221</span>        <span class="keywordflow">return</span> *m_queue;</div>
<div class="line"><a id="l00222" name="l00222"></a><span class="lineno">  222</span>    }</div>
<div class="line"><a id="l00223" name="l00223"></a><span class="lineno">  223</span>    <span class="comment"></span></div>
<div class="line"><a id="l00224" name="l00224"></a><span class="lineno">  224</span><span class="comment">    ///\brief Returns the underlying storage structure for low level access</span></div>
<div class="line"><a id="l00225" name="l00225"></a><span class="lineno">  225</span><span class="comment"></span>    storage_type raw_storage()<span class="keyword"> const</span>{</div>
<div class="line"><a id="l00226" name="l00226"></a><span class="lineno">  226</span>        <span class="keywordflow">return</span> {m_storage.buffer, m_storage.offset, m_storage.leading_dimension};</div>
<div class="line"><a id="l00227" name="l00227"></a><span class="lineno">  227</span>    }</div>
<div class="line"><a id="l00228" name="l00228"></a><span class="lineno">  228</span>    </div>
<div class="line"><a id="l00229" name="l00229"></a><span class="lineno">  229</span>    <span class="keywordtype">void</span> clear(){</div>
<div class="line"><a id="l00230" name="l00230"></a><span class="lineno">  230</span>        gpu::detail::meta_kernel k(<span class="stringliteral">&quot;matrix_proxy_clear&quot;</span>);</div>
<div class="line"><a id="l00231" name="l00231"></a><span class="lineno">  231</span>        <span class="keyword">auto</span> m = k.register_args(to_functor(*<span class="keyword">this</span>));</div>
<div class="line"><a id="l00232" name="l00232"></a><span class="lineno">  232</span>    </div>
<div class="line"><a id="l00233" name="l00233"></a><span class="lineno">  233</span>        <span class="comment">//create source</span></div>
<div class="line"><a id="l00234" name="l00234"></a><span class="lineno">  234</span>        k&lt;&lt;m(k.get_global_id(0),k.get_global_id(1))&lt;&lt;<span class="stringliteral">&quot; = 0;&quot;</span>;</div>
<div class="line"><a id="l00235" name="l00235"></a><span class="lineno">  235</span>        boost::compute::kernel kernel = k.compile(queue().get_context());</div>
<div class="line"><a id="l00236" name="l00236"></a><span class="lineno">  236</span>        <span class="comment">//enqueue kernel</span></div>
<div class="line"><a id="l00237" name="l00237"></a><span class="lineno">  237</span>        std::size_t global_work_size[2] = {size1(), size2()};</div>
<div class="line"><a id="l00238" name="l00238"></a><span class="lineno">  238</span>        queue().enqueue_nd_range_kernel(kernel, 2,<span class="keyword">nullptr</span>, global_work_size, <span class="keyword">nullptr</span>);</div>
<div class="line"><a id="l00239" name="l00239"></a><span class="lineno">  239</span>    }</div>
<div class="line"><a id="l00240" name="l00240"></a><span class="lineno">  240</span>    </div>
<div class="line"><a id="l00241" name="l00241"></a><span class="lineno">  241</span>    <span class="comment">// Iterator types</span></div>
<div class="line"><a id="l00242" name="l00242"></a><span class="lineno">  242</span>    <span class="keyword">typedef</span> no_iterator major_iterator;</div>
<div class="line"><a id="l00243" name="l00243"></a><span class="lineno">  243</span>    <span class="keyword">typedef</span> no_iterator const_major_iterator;</div>
<div class="line"><a id="l00244" name="l00244"></a><span class="lineno">  244</span> </div>
<div class="line"><a id="l00245" name="l00245"></a><span class="lineno">  245</span> </div>
<div class="line"><a id="l00246" name="l00246"></a><span class="lineno">  246</span><span class="keyword">private</span>:</div>
<div class="line"><a id="l00247" name="l00247"></a><span class="lineno">  247</span>    storage_type m_storage;</div>
<div class="line"><a id="l00248" name="l00248"></a><span class="lineno">  248</span>    boost::compute::command_queue* m_queue;</div>
<div class="line"><a id="l00249" name="l00249"></a><span class="lineno">  249</span>    size_type m_size1;</div>
<div class="line"><a id="l00250" name="l00250"></a><span class="lineno">  250</span>    size_type m_size2;</div>
<div class="line"><a id="l00251" name="l00251"></a><span class="lineno">  251</span>};  </div>
<div class="line"><a id="l00252" name="l00252"></a><span class="lineno">  252</span>    </div>
<div class="line"><a id="l00253" name="l00253"></a><span class="lineno">  253</span><span class="keyword">template</span>&lt;<span class="keyword">class</span> T&gt;</div>
<div class="line"><a id="l00254" name="l00254"></a><span class="lineno">  254</span><span class="keyword">class </span>vector&lt;T, gpu_tag&gt;: <span class="keyword">public</span> vector_container&lt;vector&lt;T, gpu_tag&gt;, gpu_tag &gt; {</div>
<div class="line"><a id="l00255" name="l00255"></a><span class="lineno">  255</span><span class="keyword">public</span>:</div>
<div class="line"><a id="l00256" name="l00256"></a><span class="lineno">  256</span>    <span class="keyword">typedef</span> T value_type;</div>
<div class="line"><a id="l00257" name="l00257"></a><span class="lineno">  257</span>    <span class="keyword">typedef</span> value_type const_reference;</div>
<div class="line"><a id="l00258" name="l00258"></a><span class="lineno">  258</span>    <span class="keyword">typedef</span> value_type reference;</div>
<div class="line"><a id="l00259" name="l00259"></a><span class="lineno">  259</span>    <span class="keyword">typedef</span> std::size_t size_type;</div>
<div class="line"><a id="l00260" name="l00260"></a><span class="lineno">  260</span> </div>
<div class="line"><a id="l00261" name="l00261"></a><span class="lineno">  261</span>    <span class="keyword">typedef</span> dense_vector_adaptor&lt;T const, continuous_dense_tag, gpu_tag&gt; const_closure_type;</div>
<div class="line"><a id="l00262" name="l00262"></a><span class="lineno">  262</span>    <span class="keyword">typedef</span> dense_vector_adaptor&lt;T, continuous_dense_tag, gpu_tag&gt; closure_type;</div>
<div class="line"><a id="l00263" name="l00263"></a><span class="lineno">  263</span>    <span class="keyword">typedef</span> gpu::dense_vector_storage&lt;T,continuous_dense_tag&gt; storage_type;</div>
<div class="line"><a id="l00264" name="l00264"></a><span class="lineno">  264</span>    <span class="keyword">typedef</span> gpu::dense_vector_storage&lt;T,continuous_dense_tag&gt; const_storage_type;</div>
<div class="line"><a id="l00265" name="l00265"></a><span class="lineno">  265</span>    <span class="keyword">typedef</span> elementwise&lt;dense_tag&gt; evaluation_category;</div>
<div class="line"><a id="l00266" name="l00266"></a><span class="lineno">  266</span> </div>
<div class="line"><a id="l00267" name="l00267"></a><span class="lineno">  267</span>    <span class="comment">// Construction and destruction</span></div>
<div class="line"><a id="l00268" name="l00268"></a><span class="lineno">  268</span><span class="comment"></span> </div>
<div class="line"><a id="l00269" name="l00269"></a><span class="lineno">  269</span><span class="comment">    /// \brief Constructor of a vector with a default queue</span></div>
<div class="line"><a id="l00270" name="l00270"></a><span class="lineno">  270</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00271" name="l00271"></a><span class="lineno">  271</span><span class="comment">    ///note that for all operations for which vector is on the left hand side,</span></div>
<div class="line"><a id="l00272" name="l00272"></a><span class="lineno">  272</span><span class="comment">    ///the kernels are enqueued on the supplied queue in case of a multi-queue setup.</span></div>
<div class="line"><a id="l00273" name="l00273"></a><span class="lineno">  273</span><span class="comment"></span>    vector(boost::compute::command_queue&amp; queue = boost::compute::system::default_queue())</div>
<div class="line"><a id="l00274" name="l00274"></a><span class="lineno">  274</span>    :m_storage(queue.get_context()), m_queue(&amp;queue){}</div>
<div class="line"><a id="l00275" name="l00275"></a><span class="lineno">  275</span><span class="comment"></span> </div>
<div class="line"><a id="l00276" name="l00276"></a><span class="lineno">  276</span><span class="comment">    /// \brief Constructor of a vector with a predefined size</span></div>
<div class="line"><a id="l00277" name="l00277"></a><span class="lineno">  277</span><span class="comment">    /// By default, its elements are uninitialized.</span></div>
<div class="line"><a id="l00278" name="l00278"></a><span class="lineno">  278</span><span class="comment">    /// \param size initial size of the vector</span></div>
<div class="line"><a id="l00279" name="l00279"></a><span class="lineno">  279</span><span class="comment">    /// \param queue the opencl queue to use by this vector</span></div>
<div class="line"><a id="l00280" name="l00280"></a><span class="lineno">  280</span><span class="comment"></span>    <span class="keyword">explicit</span> vector(size_type size, boost::compute::command_queue&amp; queue = boost::compute::system::default_queue())</div>
<div class="line"><a id="l00281" name="l00281"></a><span class="lineno">  281</span>    : m_storage(size,queue.get_context()), m_queue(&amp;queue){}</div>
<div class="line"><a id="l00282" name="l00282"></a><span class="lineno">  282</span><span class="comment"></span> </div>
<div class="line"><a id="l00283" name="l00283"></a><span class="lineno">  283</span><span class="comment">    /// \brief Constructor of a vector with a predefined size and a unique initial value</span></div>
<div class="line"><a id="l00284" name="l00284"></a><span class="lineno">  284</span><span class="comment">    /// \param size of the vector</span></div>
<div class="line"><a id="l00285" name="l00285"></a><span class="lineno">  285</span><span class="comment">    /// \param init value to assign to each element of the vector</span></div>
<div class="line"><a id="l00286" name="l00286"></a><span class="lineno">  286</span><span class="comment">    /// \param queue the opencl queue to use by this vector</span></div>
<div class="line"><a id="l00287" name="l00287"></a><span class="lineno">  287</span><span class="comment"></span>    vector(size_type size, value_type <span class="keyword">const</span>&amp; init, boost::compute::command_queue&amp; queue = boost::compute::system::default_queue())</div>
<div class="line"><a id="l00288" name="l00288"></a><span class="lineno">  288</span>    : m_storage(size, init, queue), m_queue(&amp;queue){}</div>
<div class="line"><a id="l00289" name="l00289"></a><span class="lineno">  289</span>    <span class="comment"></span></div>
<div class="line"><a id="l00290" name="l00290"></a><span class="lineno">  290</span><span class="comment">    /// \brief Move-constructor of a vector</span></div>
<div class="line"><a id="l00291" name="l00291"></a><span class="lineno">  291</span><span class="comment">    /// \param v is the vector to be moved</span></div>
<div class="line"><a id="l00292" name="l00292"></a><span class="lineno">  292</span><span class="comment"></span>    vector(vector &amp;&amp; v)</div>
<div class="line"><a id="l00293" name="l00293"></a><span class="lineno">  293</span>    : m_storage(std::move(v.m_storage))</div>
<div class="line"><a id="l00294" name="l00294"></a><span class="lineno">  294</span>    , m_queue(&amp;v.queue()){}</div>
<div class="line"><a id="l00295" name="l00295"></a><span class="lineno">  295</span><span class="comment"></span> </div>
<div class="line"><a id="l00296" name="l00296"></a><span class="lineno">  296</span><span class="comment">    /// \brief Copy-constructor of a vector</span></div>
<div class="line"><a id="l00297" name="l00297"></a><span class="lineno">  297</span><span class="comment">    /// \param v is the vector to be duplicated</span></div>
<div class="line"><a id="l00298" name="l00298"></a><span class="lineno">  298</span><span class="comment"></span>    vector(vector <span class="keyword">const</span>&amp; v) = <span class="keywordflow">default</span>;</div>
<div class="line"><a id="l00299" name="l00299"></a><span class="lineno">  299</span><span class="comment"></span> </div>
<div class="line"><a id="l00300" name="l00300"></a><span class="lineno">  300</span><span class="comment">    /// \brief Copy-constructor of a vector from a vector_expression</span></div>
<div class="line"><a id="l00301" name="l00301"></a><span class="lineno">  301</span><span class="comment">    /// \param e the vector_expression whose values will be duplicated into the vector</span></div>
<div class="line"><a id="l00302" name="l00302"></a><span class="lineno">  302</span><span class="comment"></span>    <span class="keyword">template</span>&lt;<span class="keyword">class</span> E&gt;</div>
<div class="line"><a id="l00303" name="l00303"></a><span class="lineno">  303</span>    vector(vector_expression&lt;E, gpu_tag&gt; <span class="keyword">const</span>&amp; e)</div>
<div class="line"><a id="l00304" name="l00304"></a><span class="lineno">  304</span>    : m_storage(e().size(), e().queue().get_context())</div>
<div class="line"><a id="l00305" name="l00305"></a><span class="lineno">  305</span>    , m_queue(&amp;e().queue()){</div>
<div class="line"><a id="l00306" name="l00306"></a><span class="lineno">  306</span>        assign(*<span class="keyword">this</span>, e);</div>
<div class="line"><a id="l00307" name="l00307"></a><span class="lineno">  307</span>    }</div>
<div class="line"><a id="l00308" name="l00308"></a><span class="lineno">  308</span>    <span class="comment"></span></div>
<div class="line"><a id="l00309" name="l00309"></a><span class="lineno">  309</span><span class="comment">    /// \brief Copy-constructor of a vector from a vector_expression on a given queue</span></div>
<div class="line"><a id="l00310" name="l00310"></a><span class="lineno">  310</span><span class="comment">    /// \param e the vector_expression whose values will be duplicated into the vector</span></div>
<div class="line"><a id="l00311" name="l00311"></a><span class="lineno">  311</span><span class="comment">    /// \param queue the queue which should perform the task</span></div>
<div class="line"><a id="l00312" name="l00312"></a><span class="lineno">  312</span><span class="comment"></span>    <span class="keyword">template</span>&lt;<span class="keyword">class</span> E&gt;</div>
<div class="line"><a id="l00313" name="l00313"></a><span class="lineno">  313</span>    vector(vector_expression&lt;E, gpu_tag&gt; <span class="keyword">const</span>&amp; e, boost::compute::command_queue&amp; queue)</div>
<div class="line"><a id="l00314" name="l00314"></a><span class="lineno">  314</span>    : m_storage(e().size(), queue.get_context())</div>
<div class="line"><a id="l00315" name="l00315"></a><span class="lineno">  315</span>    , m_queue(&amp;queue){</div>
<div class="line"><a id="l00316" name="l00316"></a><span class="lineno">  316</span>        assign(*<span class="keyword">this</span>, e);</div>
<div class="line"><a id="l00317" name="l00317"></a><span class="lineno">  317</span>    }</div>
<div class="line"><a id="l00318" name="l00318"></a><span class="lineno">  318</span>    </div>
<div class="line"><a id="l00319" name="l00319"></a><span class="lineno">  319</span>    <span class="comment">// Element access</span></div>
<div class="line"><a id="l00320" name="l00320"></a><span class="lineno">  320</span>    gpu::detail::dense_vector_element&lt;value_type&gt; to_functor()<span class="keyword"> const</span>{</div>
<div class="line"><a id="l00321" name="l00321"></a><span class="lineno">  321</span>        <span class="keywordflow">return</span>  {m_storage.get_buffer()}; </div>
<div class="line"><a id="l00322" name="l00322"></a><span class="lineno">  322</span>    }</div>
<div class="line"><a id="l00323" name="l00323"></a><span class="lineno">  323</span>    </div>
<div class="line"><a id="l00324" name="l00324"></a><span class="lineno">  324</span>    <span class="comment">// -------------------</span></div>
<div class="line"><a id="l00325" name="l00325"></a><span class="lineno">  325</span>    <span class="comment">// Assignment operators</span></div>
<div class="line"><a id="l00326" name="l00326"></a><span class="lineno">  326</span>    <span class="comment">// -------------------</span></div>
<div class="line"><a id="l00327" name="l00327"></a><span class="lineno">  327</span>    <span class="comment"></span></div>
<div class="line"><a id="l00328" name="l00328"></a><span class="lineno">  328</span><span class="comment">    /// \brief Assign a full vector (\e RHS-vector) to the current vector (\e LHS-vector)</span></div>
<div class="line"><a id="l00329" name="l00329"></a><span class="lineno">  329</span><span class="comment">    /// Assign a full vector (\e RHS-vector) to the current vector (\e LHS-vector). This method does not create any temporary.</span></div>
<div class="line"><a id="l00330" name="l00330"></a><span class="lineno">  330</span><span class="comment">    /// \param v is the source vector container</span></div>
<div class="line"><a id="l00331" name="l00331"></a><span class="lineno">  331</span><span class="comment">    /// \return a reference to a vector (i.e. the destination vector)</span></div>
<div class="line"><a id="l00332" name="l00332"></a><span class="lineno">  332</span><span class="comment"></span>    vector&amp; operator = (vector <span class="keyword">const</span>&amp; v){</div>
<div class="line"><a id="l00333" name="l00333"></a><span class="lineno">  333</span>        resize(v.size());</div>
<div class="line"><a id="l00334" name="l00334"></a><span class="lineno">  334</span>        <span class="keywordflow">return</span> assign(*<span class="keyword">this</span>, v);</div>
<div class="line"><a id="l00335" name="l00335"></a><span class="lineno">  335</span>    }</div>
<div class="line"><a id="l00336" name="l00336"></a><span class="lineno">  336</span>    <span class="comment"></span></div>
<div class="line"><a id="l00337" name="l00337"></a><span class="lineno">  337</span><span class="comment">    /// \brief Move-Assign a full vector (\e RHS-vector) to the current vector (\e LHS-vector)</span></div>
<div class="line"><a id="l00338" name="l00338"></a><span class="lineno">  338</span><span class="comment">    /// \param v is the source vector container</span></div>
<div class="line"><a id="l00339" name="l00339"></a><span class="lineno">  339</span><span class="comment">    /// \return a reference to a vector (i.e. the destination vector)</span></div>
<div class="line"><a id="l00340" name="l00340"></a><span class="lineno">  340</span><span class="comment"></span>    vector&amp; operator = (vector &amp;&amp; v){</div>
<div class="line"><a id="l00341" name="l00341"></a><span class="lineno">  341</span>        m_storage = std::move(v.m_storage);</div>
<div class="line"><a id="l00342" name="l00342"></a><span class="lineno">  342</span>        m_queue = v.m_queue;</div>
<div class="line"><a id="l00343" name="l00343"></a><span class="lineno">  343</span>        <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div>
<div class="line"><a id="l00344" name="l00344"></a><span class="lineno">  344</span>    }</div>
<div class="line"><a id="l00345" name="l00345"></a><span class="lineno">  345</span>    <span class="comment"></span></div>
<div class="line"><a id="l00346" name="l00346"></a><span class="lineno">  346</span><span class="comment">    /// \brief Assign a full vector (\e RHS-vector) to the current vector (\e LHS-vector)</span></div>
<div class="line"><a id="l00347" name="l00347"></a><span class="lineno">  347</span><span class="comment">    /// Assign a full vector (\e RHS-vector) to the current vector (\e LHS-vector). This method does not create any temporary.</span></div>
<div class="line"><a id="l00348" name="l00348"></a><span class="lineno">  348</span><span class="comment">    /// \param v is the source vector container</span></div>
<div class="line"><a id="l00349" name="l00349"></a><span class="lineno">  349</span><span class="comment">    /// \return a reference to a vector (i.e. the destination vector)</span></div>
<div class="line"><a id="l00350" name="l00350"></a><span class="lineno">  350</span><span class="comment"></span>    <span class="keyword">template</span>&lt;<span class="keyword">class</span> C&gt;          <span class="comment">// Container assignment without temporary</span></div>
<div class="line"><a id="l00351" name="l00351"></a><span class="lineno">  351</span>    vector&amp; operator = (vector_container&lt;C, gpu_tag&gt; <span class="keyword">const</span>&amp; v) {</div>
<div class="line"><a id="l00352" name="l00352"></a><span class="lineno">  352</span>        resize(v().size());</div>
<div class="line"><a id="l00353" name="l00353"></a><span class="lineno">  353</span>        <span class="keywordflow">return</span> assign(*<span class="keyword">this</span>, v);</div>
<div class="line"><a id="l00354" name="l00354"></a><span class="lineno">  354</span>    }</div>
<div class="line"><a id="l00355" name="l00355"></a><span class="lineno">  355</span><span class="comment"></span> </div>
<div class="line"><a id="l00356" name="l00356"></a><span class="lineno">  356</span><span class="comment">    /// \brief Assign the result of a vector_expression to the vector</span></div>
<div class="line"><a id="l00357" name="l00357"></a><span class="lineno">  357</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00358" name="l00358"></a><span class="lineno">  358</span><span class="comment">    /// \param e is a const reference to the vector_expression</span></div>
<div class="line"><a id="l00359" name="l00359"></a><span class="lineno">  359</span><span class="comment">    /// \return a reference to the resulting vector</span></div>
<div class="line"><a id="l00360" name="l00360"></a><span class="lineno">  360</span><span class="comment"></span>    <span class="keyword">template</span>&lt;<span class="keyword">class</span> E&gt;</div>
<div class="line"><a id="l00361" name="l00361"></a><span class="lineno">  361</span>    vector&amp; operator = (vector_expression&lt;E, gpu_tag&gt; <span class="keyword">const</span>&amp; e) {</div>
<div class="line"><a id="l00362" name="l00362"></a><span class="lineno">  362</span>        vector temporary(e,queue());</div>
<div class="line"><a id="l00363" name="l00363"></a><span class="lineno">  363</span>        <a class="code hl_function" href="namespaceshark.html#a3fffe112e8e09ea8f41e4fb7113e93ee" title="Swaps the contents of two instances of KeyValuePair.">swap</a>(*<span class="keyword">this</span>,temporary);</div>
<div class="line"><a id="l00364" name="l00364"></a><span class="lineno">  364</span>        <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div>
<div class="line"><a id="l00365" name="l00365"></a><span class="lineno">  365</span>    }</div>
<div class="line"><a id="l00366" name="l00366"></a><span class="lineno">  366</span> </div>
<div class="line"><a id="l00367" name="l00367"></a><span class="lineno">  367</span>    <span class="comment">// ---------</span></div>
<div class="line"><a id="l00368" name="l00368"></a><span class="lineno">  368</span>    <span class="comment">// Storage interface</span></div>
<div class="line"><a id="l00369" name="l00369"></a><span class="lineno">  369</span>    <span class="comment">// ---------</span></div>
<div class="line"><a id="l00370" name="l00370"></a><span class="lineno">  370</span>    <span class="comment"></span></div>
<div class="line"><a id="l00371" name="l00371"></a><span class="lineno">  371</span><span class="comment">    /// \brief Return the size of the vector.</span></div>
<div class="line"><a id="l00372" name="l00372"></a><span class="lineno">  372</span><span class="comment"></span>    size_type size()<span class="keyword"> const </span>{</div>
<div class="line"><a id="l00373" name="l00373"></a><span class="lineno">  373</span>        <span class="keywordflow">return</span> m_storage.size();</div>
<div class="line"><a id="l00374" name="l00374"></a><span class="lineno">  374</span>    }</div>
<div class="line"><a id="l00375" name="l00375"></a><span class="lineno">  375</span>    </div>
<div class="line"><a id="l00376" name="l00376"></a><span class="lineno">  376</span>    boost::compute::command_queue&amp; queue()<span class="keyword"> const</span>{</div>
<div class="line"><a id="l00377" name="l00377"></a><span class="lineno">  377</span>        <span class="keywordflow">return</span> *m_queue;</div>
<div class="line"><a id="l00378" name="l00378"></a><span class="lineno">  378</span>    }<span class="comment"></span></div>
<div class="line"><a id="l00379" name="l00379"></a><span class="lineno">  379</span><span class="comment">    ///\brief Returns the underlying storage structure for low level access</span></div>
<div class="line"><a id="l00380" name="l00380"></a><span class="lineno">  380</span><span class="comment"></span>    const_storage_type raw_storage()<span class="keyword"> const</span>{</div>
<div class="line"><a id="l00381" name="l00381"></a><span class="lineno">  381</span>        <span class="keywordflow">return</span> {m_storage.get_buffer(),0,1};</div>
<div class="line"><a id="l00382" name="l00382"></a><span class="lineno">  382</span>    }</div>
<div class="line"><a id="l00383" name="l00383"></a><span class="lineno">  383</span>    <span class="comment"></span></div>
<div class="line"><a id="l00384" name="l00384"></a><span class="lineno">  384</span><span class="comment">    ///\brief Returns the underlying storage structure for low level access</span></div>
<div class="line"><a id="l00385" name="l00385"></a><span class="lineno">  385</span><span class="comment"></span>    storage_type raw_storage(){</div>
<div class="line"><a id="l00386" name="l00386"></a><span class="lineno">  386</span>        <span class="keywordflow">return</span> {m_storage.get_buffer(),0,1};</div>
<div class="line"><a id="l00387" name="l00387"></a><span class="lineno">  387</span>    }</div>
<div class="line"><a id="l00388" name="l00388"></a><span class="lineno">  388</span>    <span class="comment"></span></div>
<div class="line"><a id="l00389" name="l00389"></a><span class="lineno">  389</span><span class="comment">    /// \brief Resize the vector</span></div>
<div class="line"><a id="l00390" name="l00390"></a><span class="lineno">  390</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00391" name="l00391"></a><span class="lineno">  391</span><span class="comment">    /// This might erase all data stored in the vector</span></div>
<div class="line"><a id="l00392" name="l00392"></a><span class="lineno">  392</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00393" name="l00393"></a><span class="lineno">  393</span><span class="comment">    /// \param size new size of the vector</span></div>
<div class="line"><a id="l00394" name="l00394"></a><span class="lineno">  394</span><span class="comment"></span>    <span class="keywordtype">void</span> resize(size_type size) {</div>
<div class="line"><a id="l00395" name="l00395"></a><span class="lineno">  395</span>        <span class="keywordflow">if</span>(size &lt; m_storage.size())</div>
<div class="line"><a id="l00396" name="l00396"></a><span class="lineno">  396</span>            m_storage.resize(size);</div>
<div class="line"><a id="l00397" name="l00397"></a><span class="lineno">  397</span>        <span class="keywordflow">else</span></div>
<div class="line"><a id="l00398" name="l00398"></a><span class="lineno">  398</span>            m_storage = boost::compute::vector&lt;T&gt;(size, queue().get_context());</div>
<div class="line"><a id="l00399" name="l00399"></a><span class="lineno">  399</span>    }</div>
<div class="line"><a id="l00400" name="l00400"></a><span class="lineno">  400</span>    <span class="comment"></span></div>
<div class="line"><a id="l00401" name="l00401"></a><span class="lineno">  401</span><span class="comment">    /// \brief Resize the vector</span></div>
<div class="line"><a id="l00402" name="l00402"></a><span class="lineno">  402</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00403" name="l00403"></a><span class="lineno">  403</span><span class="comment">    /// This will erase all data stored in the vector and reinitialize it with the supplied value of init</span></div>
<div class="line"><a id="l00404" name="l00404"></a><span class="lineno">  404</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00405" name="l00405"></a><span class="lineno">  405</span><span class="comment">    /// \param size new size of the vector</span></div>
<div class="line"><a id="l00406" name="l00406"></a><span class="lineno">  406</span><span class="comment">    /// \param init the value of all elements</span></div>
<div class="line"><a id="l00407" name="l00407"></a><span class="lineno">  407</span><span class="comment"></span>    <span class="keywordtype">void</span> resize(size_type size, value_type init) {</div>
<div class="line"><a id="l00408" name="l00408"></a><span class="lineno">  408</span>        resize(size);</div>
<div class="line"><a id="l00409" name="l00409"></a><span class="lineno">  409</span>        boost::compute::fill(m_storage.begin(),m_storage.end(), init);</div>
<div class="line"><a id="l00410" name="l00410"></a><span class="lineno">  410</span>    }</div>
<div class="line"><a id="l00411" name="l00411"></a><span class="lineno">  411</span>    </div>
<div class="line"><a id="l00412" name="l00412"></a><span class="lineno">  412</span>    <span class="keywordtype">void</span> clear(){</div>
<div class="line"><a id="l00413" name="l00413"></a><span class="lineno">  413</span>        boost::compute::fill(m_storage.begin(),m_storage.end(), value_type<span class="comment">/*zero*/</span>());</div>
<div class="line"><a id="l00414" name="l00414"></a><span class="lineno">  414</span>    }</div>
<div class="line"><a id="l00415" name="l00415"></a><span class="lineno">  415</span>    </div>
<div class="line"><a id="l00416" name="l00416"></a><span class="lineno">  416</span>    <span class="keywordtype">bool</span> empty()<span class="keyword">const</span>{</div>
<div class="line"><a id="l00417" name="l00417"></a><span class="lineno">  417</span>        <span class="keywordflow">return</span> m_storage.empty();</div>
<div class="line"><a id="l00418" name="l00418"></a><span class="lineno">  418</span>    }</div>
<div class="line"><a id="l00419" name="l00419"></a><span class="lineno">  419</span>    <span class="comment"></span></div>
<div class="line"><a id="l00420" name="l00420"></a><span class="lineno">  420</span><span class="comment">    /// \brief Swap the content of two vectors</span></div>
<div class="line"><a id="l00421" name="l00421"></a><span class="lineno">  421</span><span class="comment">    /// \param v1 is the first vector. It takes values from v2</span></div>
<div class="line"><a id="l00422" name="l00422"></a><span class="lineno">  422</span><span class="comment">    /// \param v2 is the second vector It takes values from v1</span></div>
<div class="line"><a id="l00423" name="l00423"></a><span class="lineno">  423</span><span class="comment"></span>    <span class="keyword">friend</span> <span class="keywordtype">void</span> <a class="code hl_function" href="namespaceshark.html#a3fffe112e8e09ea8f41e4fb7113e93ee" title="Swaps the contents of two instances of KeyValuePair.">swap</a>(vector&amp; v1, vector&amp; v2) {</div>
<div class="line"><a id="l00424" name="l00424"></a><span class="lineno">  424</span>        <span class="keyword">using </span>std::swap;</div>
<div class="line"><a id="l00425" name="l00425"></a><span class="lineno">  425</span>        <a class="code hl_function" href="namespaceshark.html#a3fffe112e8e09ea8f41e4fb7113e93ee" title="Swaps the contents of two instances of KeyValuePair.">swap</a>(v1.m_storage,v2.m_storage);</div>
<div class="line"><a id="l00426" name="l00426"></a><span class="lineno">  426</span>        std::swap(v2.m_queue,v2.m_queue);</div>
<div class="line"><a id="l00427" name="l00427"></a><span class="lineno">  427</span>    }</div>
<div class="line"><a id="l00428" name="l00428"></a><span class="lineno">  428</span>    </div>
<div class="line"><a id="l00429" name="l00429"></a><span class="lineno">  429</span>    <span class="keyword">template</span>&lt;<span class="keyword">class</span> Archive&gt;</div>
<div class="line"><a id="l00430" name="l00430"></a><span class="lineno">  430</span>    <span class="keywordtype">void</span> serialize(Archive &amp;ar, <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> file_version) {</div>
<div class="line"><a id="l00431" name="l00431"></a><span class="lineno">  431</span>    }</div>
<div class="line"><a id="l00432" name="l00432"></a><span class="lineno">  432</span>    </div>
<div class="line"><a id="l00433" name="l00433"></a><span class="lineno">  433</span>    <span class="comment">// Iterator types</span></div>
<div class="line"><a id="l00434" name="l00434"></a><span class="lineno">  434</span>    <span class="keyword">typedef</span> no_iterator iterator;</div>
<div class="line"><a id="l00435" name="l00435"></a><span class="lineno">  435</span>    <span class="keyword">typedef</span> no_iterator const_iterator;</div>
<div class="line"><a id="l00436" name="l00436"></a><span class="lineno">  436</span><span class="keyword">private</span>:</div>
<div class="line"><a id="l00437" name="l00437"></a><span class="lineno">  437</span>    boost::compute::vector&lt;T&gt; m_storage;</div>
<div class="line"><a id="l00438" name="l00438"></a><span class="lineno">  438</span>    boost::compute::command_queue* m_queue;</div>
<div class="line"><a id="l00439" name="l00439"></a><span class="lineno">  439</span>};</div>
<div class="line"><a id="l00440" name="l00440"></a><span class="lineno">  440</span><span class="comment"></span> </div>
<div class="line"><a id="l00441" name="l00441"></a><span class="lineno">  441</span><span class="comment">/// \brief A dense matrix of values of type \c T stored on the gpu</span></div>
<div class="line"><a id="l00442" name="l00442"></a><span class="lineno">  442</span><span class="comment">///</span></div>
<div class="line"><a id="l00443" name="l00443"></a><span class="lineno">  443</span><span class="comment">/// For a \f$(m \times n)\f$-dimensional matrix and \f$ 0 \leq i &lt; m, 0 \leq j &lt; n\f$, every element \f$ m_{i,j} \f$ is mapped to</span></div>
<div class="line"><a id="l00444" name="l00444"></a><span class="lineno">  444</span><span class="comment">/// the \f$(i.n + j)\f$-th element of the container for row major orientation or the \f$ (i + j.m) \f$-th element of</span></div>
<div class="line"><a id="l00445" name="l00445"></a><span class="lineno">  445</span><span class="comment">/// the container for column major orientation. In a dense matrix all elements are represented in memory in a</span></div>
<div class="line"><a id="l00446" name="l00446"></a><span class="lineno">  446</span><span class="comment">/// contiguous chunk of memory by definition.</span></div>
<div class="line"><a id="l00447" name="l00447"></a><span class="lineno">  447</span><span class="comment">///</span></div>
<div class="line"><a id="l00448" name="l00448"></a><span class="lineno">  448</span><span class="comment">/// Orientation can also be specified, otherwise a \c row_major is used.</span></div>
<div class="line"><a id="l00449" name="l00449"></a><span class="lineno">  449</span><span class="comment">///</span></div>
<div class="line"><a id="l00450" name="l00450"></a><span class="lineno">  450</span><span class="comment">/// \tparam T the type of object stored in the matrix (like double, float, complex, etc...)</span></div>
<div class="line"><a id="l00451" name="l00451"></a><span class="lineno">  451</span><span class="comment">/// \tparam L the storage organization. It can be either \c row_major or \c column_major. Default is \c row_major</span></div>
<div class="line"><a id="l00452" name="l00452"></a><span class="lineno">  452</span><span class="comment"></span><span class="keyword">template</span>&lt;<span class="keyword">class</span> T, <span class="keyword">class</span> L&gt;</div>
<div class="line"><a id="l00453" name="l00453"></a><span class="lineno">  453</span><span class="keyword">class </span>matrix&lt;T,L, gpu_tag&gt; : <span class="keyword">public</span> matrix_container&lt;matrix&lt;T,L, gpu_tag&gt;, gpu_tag &gt; {</div>
<div class="line"><a id="l00454" name="l00454"></a><span class="lineno">  454</span><span class="keyword">public</span>:</div>
<div class="line"><a id="l00455" name="l00455"></a><span class="lineno">  455</span>    <span class="keyword">typedef</span> T value_type;</div>
<div class="line"><a id="l00456" name="l00456"></a><span class="lineno">  456</span>    <span class="keyword">typedef</span> value_type const_reference;</div>
<div class="line"><a id="l00457" name="l00457"></a><span class="lineno">  457</span>    <span class="keyword">typedef</span> value_type reference;</div>
<div class="line"><a id="l00458" name="l00458"></a><span class="lineno">  458</span>    <span class="keyword">typedef</span> std::size_t size_type;</div>
<div class="line"><a id="l00459" name="l00459"></a><span class="lineno">  459</span> </div>
<div class="line"><a id="l00460" name="l00460"></a><span class="lineno">  460</span>    <span class="keyword">typedef</span> dense_matrix_adaptor&lt;T const,L, continuous_dense_tag, gpu_tag&gt; const_closure_type;</div>
<div class="line"><a id="l00461" name="l00461"></a><span class="lineno">  461</span>    <span class="keyword">typedef</span> dense_matrix_adaptor&lt;T,L, continuous_dense_tag, gpu_tag&gt; closure_type;</div>
<div class="line"><a id="l00462" name="l00462"></a><span class="lineno">  462</span>    <span class="keyword">typedef</span> gpu::dense_matrix_storage&lt;T, continuous_dense_tag&gt; storage_type;</div>
<div class="line"><a id="l00463" name="l00463"></a><span class="lineno">  463</span>    <span class="keyword">typedef</span> gpu::dense_matrix_storage&lt;T const, continuous_dense_tag&gt; const_storage_type;</div>
<div class="line"><a id="l00464" name="l00464"></a><span class="lineno">  464</span>    <span class="keyword">typedef</span> elementwise&lt;dense_tag&gt; evaluation_category;</div>
<div class="line"><a id="l00465" name="l00465"></a><span class="lineno">  465</span>    <span class="keyword">typedef</span> L orientation;</div>
<div class="line"><a id="l00466" name="l00466"></a><span class="lineno">  466</span> </div>
<div class="line"><a id="l00467" name="l00467"></a><span class="lineno">  467</span>    <span class="comment">// Construction and destruction</span></div>
<div class="line"><a id="l00468" name="l00468"></a><span class="lineno">  468</span><span class="comment"></span> </div>
<div class="line"><a id="l00469" name="l00469"></a><span class="lineno">  469</span><span class="comment">    /// \brief Constructor of a matrix with a default queue</span></div>
<div class="line"><a id="l00470" name="l00470"></a><span class="lineno">  470</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00471" name="l00471"></a><span class="lineno">  471</span><span class="comment">    ///note that for all operations for which matrix is on the left hand side,</span></div>
<div class="line"><a id="l00472" name="l00472"></a><span class="lineno">  472</span><span class="comment">    ///the kernels are enqueued on the supplied queue in case of a multi-queue setup.</span></div>
<div class="line"><a id="l00473" name="l00473"></a><span class="lineno">  473</span><span class="comment"></span>    matrix(boost::compute::command_queue&amp; queue = boost::compute::system::default_queue())</div>
<div class="line"><a id="l00474" name="l00474"></a><span class="lineno">  474</span>    : m_storage(queue.get_context())</div>
<div class="line"><a id="l00475" name="l00475"></a><span class="lineno">  475</span>    , m_queue(&amp;queue),m_size1(0), m_size2(0){}</div>
<div class="line"><a id="l00476" name="l00476"></a><span class="lineno">  476</span><span class="comment"></span> </div>
<div class="line"><a id="l00477" name="l00477"></a><span class="lineno">  477</span><span class="comment">    /// \brief Constructor of a matrix with a predefined size</span></div>
<div class="line"><a id="l00478" name="l00478"></a><span class="lineno">  478</span><span class="comment">    /// By default, its elements are uninitialized</span></div>
<div class="line"><a id="l00479" name="l00479"></a><span class="lineno">  479</span><span class="comment">    /// \param size1 number of rows</span></div>
<div class="line"><a id="l00480" name="l00480"></a><span class="lineno">  480</span><span class="comment">    /// \param size2 number of columns</span></div>
<div class="line"><a id="l00481" name="l00481"></a><span class="lineno">  481</span><span class="comment">    /// \param queue the opencl queue to use by this matrix</span></div>
<div class="line"><a id="l00482" name="l00482"></a><span class="lineno">  482</span><span class="comment"></span>    <span class="keyword">explicit</span> matrix(size_type size1, size_type size2, boost::compute::command_queue&amp; queue = boost::compute::system::default_queue())</div>
<div class="line"><a id="l00483" name="l00483"></a><span class="lineno">  483</span>    : m_storage(size1 * size2, queue.get_context())</div>
<div class="line"><a id="l00484" name="l00484"></a><span class="lineno">  484</span>    , m_queue(&amp;queue)</div>
<div class="line"><a id="l00485" name="l00485"></a><span class="lineno">  485</span>    , m_size1(size1)</div>
<div class="line"><a id="l00486" name="l00486"></a><span class="lineno">  486</span>    , m_size2(size2){}</div>
<div class="line"><a id="l00487" name="l00487"></a><span class="lineno">  487</span><span class="comment"></span> </div>
<div class="line"><a id="l00488" name="l00488"></a><span class="lineno">  488</span><span class="comment">    /// \brief Constructor of a matrix with a predefined size initialized to a value</span></div>
<div class="line"><a id="l00489" name="l00489"></a><span class="lineno">  489</span><span class="comment">    /// \param size1 number of rows</span></div>
<div class="line"><a id="l00490" name="l00490"></a><span class="lineno">  490</span><span class="comment">    /// \param size2 number of columns</span></div>
<div class="line"><a id="l00491" name="l00491"></a><span class="lineno">  491</span><span class="comment">    /// \param init value to assign to each element of the matrix</span></div>
<div class="line"><a id="l00492" name="l00492"></a><span class="lineno">  492</span><span class="comment">    /// \param queue the opencl queue to use by this matrix</span></div>
<div class="line"><a id="l00493" name="l00493"></a><span class="lineno">  493</span><span class="comment"></span>    matrix(size_type size1, size_type size2, value_type <span class="keyword">const</span>&amp; init, boost::compute::command_queue&amp; queue = boost::compute::system::default_queue())</div>
<div class="line"><a id="l00494" name="l00494"></a><span class="lineno">  494</span>    : m_storage(size1 * size2, init, queue)</div>
<div class="line"><a id="l00495" name="l00495"></a><span class="lineno">  495</span>    , m_queue(&amp;queue)</div>
<div class="line"><a id="l00496" name="l00496"></a><span class="lineno">  496</span>    , m_size1(size1)</div>
<div class="line"><a id="l00497" name="l00497"></a><span class="lineno">  497</span>    , m_size2(size2){}</div>
<div class="line"><a id="l00498" name="l00498"></a><span class="lineno">  498</span>    <span class="comment"></span></div>
<div class="line"><a id="l00499" name="l00499"></a><span class="lineno">  499</span><span class="comment">    /// \brief Move-constructor of a matrix</span></div>
<div class="line"><a id="l00500" name="l00500"></a><span class="lineno">  500</span><span class="comment">    /// \param m is the matrix to be moved</span></div>
<div class="line"><a id="l00501" name="l00501"></a><span class="lineno">  501</span><span class="comment"></span>    matrix(matrix &amp;&amp; m)</div>
<div class="line"><a id="l00502" name="l00502"></a><span class="lineno">  502</span>    : m_storage(std::move(m.m_storage))</div>
<div class="line"><a id="l00503" name="l00503"></a><span class="lineno">  503</span>    , m_queue(&amp;m.queue())</div>
<div class="line"><a id="l00504" name="l00504"></a><span class="lineno">  504</span>    , m_size1(m.size1())</div>
<div class="line"><a id="l00505" name="l00505"></a><span class="lineno">  505</span>    , m_size2(m.size2()){}</div>
<div class="line"><a id="l00506" name="l00506"></a><span class="lineno">  506</span><span class="comment"></span> </div>
<div class="line"><a id="l00507" name="l00507"></a><span class="lineno">  507</span><span class="comment">    /// \brief Copy-constructor of a matrix</span></div>
<div class="line"><a id="l00508" name="l00508"></a><span class="lineno">  508</span><span class="comment">    /// \param m is the matrix to be duplicated</span></div>
<div class="line"><a id="l00509" name="l00509"></a><span class="lineno">  509</span><span class="comment"></span>    matrix(matrix <span class="keyword">const</span>&amp; m)</div>
<div class="line"><a id="l00510" name="l00510"></a><span class="lineno">  510</span>    : m_storage(m.m_storage)</div>
<div class="line"><a id="l00511" name="l00511"></a><span class="lineno">  511</span>    , m_queue(&amp;m.queue())</div>
<div class="line"><a id="l00512" name="l00512"></a><span class="lineno">  512</span>    , m_size1(m.size1())</div>
<div class="line"><a id="l00513" name="l00513"></a><span class="lineno">  513</span>    , m_size2(m.size2()){}</div>
<div class="line"><a id="l00514" name="l00514"></a><span class="lineno">  514</span><span class="comment"></span> </div>
<div class="line"><a id="l00515" name="l00515"></a><span class="lineno">  515</span><span class="comment">    /// \brief Copy-constructor of a matrix from a matrix_expression</span></div>
<div class="line"><a id="l00516" name="l00516"></a><span class="lineno">  516</span><span class="comment">    /// \param e the matrix_expression whose values will be duplicated into the matrix</span></div>
<div class="line"><a id="l00517" name="l00517"></a><span class="lineno">  517</span><span class="comment"></span>    <span class="keyword">template</span>&lt;<span class="keyword">class</span> E&gt;</div>
<div class="line"><a id="l00518" name="l00518"></a><span class="lineno">  518</span>    matrix(matrix_expression&lt;E, gpu_tag&gt; <span class="keyword">const</span>&amp; e)</div>
<div class="line"><a id="l00519" name="l00519"></a><span class="lineno">  519</span>    : m_storage(e().size1() * e().size2(), e().queue().get_context())</div>
<div class="line"><a id="l00520" name="l00520"></a><span class="lineno">  520</span>    , m_queue(&amp;e().queue())</div>
<div class="line"><a id="l00521" name="l00521"></a><span class="lineno">  521</span>    , m_size1(e().size1())</div>
<div class="line"><a id="l00522" name="l00522"></a><span class="lineno">  522</span>    , m_size2(e().size2()){</div>
<div class="line"><a id="l00523" name="l00523"></a><span class="lineno">  523</span>        assign(*<span class="keyword">this</span>, e);</div>
<div class="line"><a id="l00524" name="l00524"></a><span class="lineno">  524</span>    }</div>
<div class="line"><a id="l00525" name="l00525"></a><span class="lineno">  525</span>    </div>
<div class="line"><a id="l00526" name="l00526"></a><span class="lineno">  526</span>    <span class="keyword">template</span>&lt;<span class="keyword">class</span> E&gt;</div>
<div class="line"><a id="l00527" name="l00527"></a><span class="lineno">  527</span>    matrix(vector_set_expression&lt;E, gpu_tag&gt; <span class="keyword">const</span>&amp; e)</div>
<div class="line"><a id="l00528" name="l00528"></a><span class="lineno">  528</span>    : m_storage(e().size() * e().point_size(), e().queue().get_context())</div>
<div class="line"><a id="l00529" name="l00529"></a><span class="lineno">  529</span>    , m_queue(&amp;e().queue())</div>
<div class="line"><a id="l00530" name="l00530"></a><span class="lineno">  530</span>    , m_size1(E::point_orientation::index_M(e().size(), e().point_size()))</div>
<div class="line"><a id="l00531" name="l00531"></a><span class="lineno">  531</span>    , m_size2(E::point_orientation::index_m(e().size(), e().point_size())){</div>
<div class="line"><a id="l00532" name="l00532"></a><span class="lineno">  532</span>        assign(*<span class="keyword">this</span>, e().expression());</div>
<div class="line"><a id="l00533" name="l00533"></a><span class="lineno">  533</span>    }</div>
<div class="line"><a id="l00534" name="l00534"></a><span class="lineno">  534</span>    </div>
<div class="line"><a id="l00535" name="l00535"></a><span class="lineno">  535</span>    <span class="comment">// -------------------</span></div>
<div class="line"><a id="l00536" name="l00536"></a><span class="lineno">  536</span>    <span class="comment">// Assignment operators</span></div>
<div class="line"><a id="l00537" name="l00537"></a><span class="lineno">  537</span>    <span class="comment">// -------------------</span></div>
<div class="line"><a id="l00538" name="l00538"></a><span class="lineno">  538</span>    <span class="comment"></span></div>
<div class="line"><a id="l00539" name="l00539"></a><span class="lineno">  539</span><span class="comment">    /// \brief Assign a full matrix (\e RHS-matrix) to the current matrix (\e LHS-matrix)</span></div>
<div class="line"><a id="l00540" name="l00540"></a><span class="lineno">  540</span><span class="comment">    /// Assign a full matrix (\e RHS-matrix) to the current matrix (\e LHS-matrix). This method does not create any temporary.</span></div>
<div class="line"><a id="l00541" name="l00541"></a><span class="lineno">  541</span><span class="comment">    /// \param m is the source matrix container</span></div>
<div class="line"><a id="l00542" name="l00542"></a><span class="lineno">  542</span><span class="comment">    /// \return a reference to a matrix (i.e. the destination matrix)</span></div>
<div class="line"><a id="l00543" name="l00543"></a><span class="lineno">  543</span><span class="comment"></span>    matrix&amp; operator = (matrix <span class="keyword">const</span>&amp; m){</div>
<div class="line"><a id="l00544" name="l00544"></a><span class="lineno">  544</span>        resize(m.size1(),m.size2());</div>
<div class="line"><a id="l00545" name="l00545"></a><span class="lineno">  545</span>        <span class="keywordflow">return</span> assign(*<span class="keyword">this</span>, m);</div>
<div class="line"><a id="l00546" name="l00546"></a><span class="lineno">  546</span>    }</div>
<div class="line"><a id="l00547" name="l00547"></a><span class="lineno">  547</span>    <span class="comment"></span></div>
<div class="line"><a id="l00548" name="l00548"></a><span class="lineno">  548</span><span class="comment">    /// \brief Move-Assign a full matrix (\e RHS-matrix) to the current matrix (\e LHS-matrix)</span></div>
<div class="line"><a id="l00549" name="l00549"></a><span class="lineno">  549</span><span class="comment">    /// \param m is the source matrix container</span></div>
<div class="line"><a id="l00550" name="l00550"></a><span class="lineno">  550</span><span class="comment">    /// \return a reference to a matrix (i.e. the destination matrix)</span></div>
<div class="line"><a id="l00551" name="l00551"></a><span class="lineno">  551</span><span class="comment"></span>    matrix&amp; operator = (matrix &amp;&amp; m){</div>
<div class="line"><a id="l00552" name="l00552"></a><span class="lineno">  552</span>        m_storage = std::move(m.m_storage);</div>
<div class="line"><a id="l00553" name="l00553"></a><span class="lineno">  553</span>        m_queue = m.m_queue;</div>
<div class="line"><a id="l00554" name="l00554"></a><span class="lineno">  554</span>        m_size1 = m.m_size1;</div>
<div class="line"><a id="l00555" name="l00555"></a><span class="lineno">  555</span>        m_size2 = m.m_size2;</div>
<div class="line"><a id="l00556" name="l00556"></a><span class="lineno">  556</span>        <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div>
<div class="line"><a id="l00557" name="l00557"></a><span class="lineno">  557</span>    }</div>
<div class="line"><a id="l00558" name="l00558"></a><span class="lineno">  558</span>    <span class="comment"></span></div>
<div class="line"><a id="l00559" name="l00559"></a><span class="lineno">  559</span><span class="comment">    /// \brief Assign a full matrix (\e RHS-matrix) to the current matrix (\e LHS-matrix)</span></div>
<div class="line"><a id="l00560" name="l00560"></a><span class="lineno">  560</span><span class="comment">    /// Assign a full matrix (\e RHS-matrix) to the current matrix (\e LHS-matrix). This method does not create any temporary.</span></div>
<div class="line"><a id="l00561" name="l00561"></a><span class="lineno">  561</span><span class="comment">    /// \param m is the source matrix container</span></div>
<div class="line"><a id="l00562" name="l00562"></a><span class="lineno">  562</span><span class="comment">    /// \return a reference to a matrix (i.e. the destination matrix)</span></div>
<div class="line"><a id="l00563" name="l00563"></a><span class="lineno">  563</span><span class="comment"></span>    <span class="keyword">template</span>&lt;<span class="keyword">class</span> C&gt;          <span class="comment">// Container assignment without temporary</span></div>
<div class="line"><a id="l00564" name="l00564"></a><span class="lineno">  564</span>    matrix&amp; operator = (matrix_container&lt;C, gpu_tag&gt; <span class="keyword">const</span>&amp; m) {</div>
<div class="line"><a id="l00565" name="l00565"></a><span class="lineno">  565</span>        resize(m().size1(), m().size2());</div>
<div class="line"><a id="l00566" name="l00566"></a><span class="lineno">  566</span>        <span class="keywordflow">return</span> assign(*<span class="keyword">this</span>, m);</div>
<div class="line"><a id="l00567" name="l00567"></a><span class="lineno">  567</span>    }</div>
<div class="line"><a id="l00568" name="l00568"></a><span class="lineno">  568</span><span class="comment"></span> </div>
<div class="line"><a id="l00569" name="l00569"></a><span class="lineno">  569</span><span class="comment">    /// \brief Assign the result of a matrix_expression to the matrix</span></div>
<div class="line"><a id="l00570" name="l00570"></a><span class="lineno">  570</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00571" name="l00571"></a><span class="lineno">  571</span><span class="comment">    /// \param e is a const reference to the matrix_expression</span></div>
<div class="line"><a id="l00572" name="l00572"></a><span class="lineno">  572</span><span class="comment">    /// \return a reference to the resulting matrix</span></div>
<div class="line"><a id="l00573" name="l00573"></a><span class="lineno">  573</span><span class="comment"></span>    <span class="keyword">template</span>&lt;<span class="keyword">class</span> E&gt;</div>
<div class="line"><a id="l00574" name="l00574"></a><span class="lineno">  574</span>    matrix&amp; operator = (matrix_expression&lt;E, gpu_tag&gt; <span class="keyword">const</span>&amp; e) {</div>
<div class="line"><a id="l00575" name="l00575"></a><span class="lineno">  575</span>        matrix temporary(e);</div>
<div class="line"><a id="l00576" name="l00576"></a><span class="lineno">  576</span>        <a class="code hl_function" href="namespaceshark.html#a3fffe112e8e09ea8f41e4fb7113e93ee" title="Swaps the contents of two instances of KeyValuePair.">swap</a>(*<span class="keyword">this</span>,temporary);</div>
<div class="line"><a id="l00577" name="l00577"></a><span class="lineno">  577</span>        <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div>
<div class="line"><a id="l00578" name="l00578"></a><span class="lineno">  578</span>    }</div>
<div class="line"><a id="l00579" name="l00579"></a><span class="lineno">  579</span>    </div>
<div class="line"><a id="l00580" name="l00580"></a><span class="lineno">  580</span>    <span class="comment"></span></div>
<div class="line"><a id="l00581" name="l00581"></a><span class="lineno">  581</span><span class="comment">    /// \brief Assign the result of a vector_set to the matrix</span></div>
<div class="line"><a id="l00582" name="l00582"></a><span class="lineno">  582</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00583" name="l00583"></a><span class="lineno">  583</span><span class="comment">    /// \param e is a const reference to the vector_set_expression</span></div>
<div class="line"><a id="l00584" name="l00584"></a><span class="lineno">  584</span><span class="comment">    /// \return a reference to the resulting matrix</span></div>
<div class="line"><a id="l00585" name="l00585"></a><span class="lineno">  585</span><span class="comment"></span>    <span class="keyword">template</span>&lt;<span class="keyword">class</span> E&gt;</div>
<div class="line"><a id="l00586" name="l00586"></a><span class="lineno">  586</span>    matrix&amp; operator = (vector_set_expression&lt;E, gpu_tag&gt; <span class="keyword">const</span>&amp; e) {</div>
<div class="line"><a id="l00587" name="l00587"></a><span class="lineno">  587</span>        matrix temporary(e);</div>
<div class="line"><a id="l00588" name="l00588"></a><span class="lineno">  588</span>        <a class="code hl_function" href="namespaceshark.html#a3fffe112e8e09ea8f41e4fb7113e93ee" title="Swaps the contents of two instances of KeyValuePair.">swap</a>(temporary);</div>
<div class="line"><a id="l00589" name="l00589"></a><span class="lineno">  589</span>        <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div>
<div class="line"><a id="l00590" name="l00590"></a><span class="lineno">  590</span>    }</div>
<div class="line"><a id="l00591" name="l00591"></a><span class="lineno">  591</span> </div>
<div class="line"><a id="l00592" name="l00592"></a><span class="lineno">  592</span>    <span class="comment">// ---------</span></div>
<div class="line"><a id="l00593" name="l00593"></a><span class="lineno">  593</span>    <span class="comment">// Storage interface</span></div>
<div class="line"><a id="l00594" name="l00594"></a><span class="lineno">  594</span>    <span class="comment">// ---------</span></div>
<div class="line"><a id="l00595" name="l00595"></a><span class="lineno">  595</span>    <span class="comment"></span></div>
<div class="line"><a id="l00596" name="l00596"></a><span class="lineno">  596</span><span class="comment">    ///\brief Returns the number of rows of the matrix.</span></div>
<div class="line"><a id="l00597" name="l00597"></a><span class="lineno">  597</span><span class="comment"></span>    size_type size1()<span class="keyword"> const </span>{</div>
<div class="line"><a id="l00598" name="l00598"></a><span class="lineno">  598</span>        <span class="keywordflow">return</span> m_size1;</div>
<div class="line"><a id="l00599" name="l00599"></a><span class="lineno">  599</span>    }<span class="comment"></span></div>
<div class="line"><a id="l00600" name="l00600"></a><span class="lineno">  600</span><span class="comment">    ///\brief Returns the number of columns of the matrix.</span></div>
<div class="line"><a id="l00601" name="l00601"></a><span class="lineno">  601</span><span class="comment"></span>    size_type size2()<span class="keyword"> const </span>{</div>
<div class="line"><a id="l00602" name="l00602"></a><span class="lineno">  602</span>        <span class="keywordflow">return</span> m_size2;</div>
<div class="line"><a id="l00603" name="l00603"></a><span class="lineno">  603</span>    }</div>
<div class="line"><a id="l00604" name="l00604"></a><span class="lineno">  604</span>    </div>
<div class="line"><a id="l00605" name="l00605"></a><span class="lineno">  605</span>    boost::compute::command_queue&amp; queue()<span class="keyword"> const</span>{</div>
<div class="line"><a id="l00606" name="l00606"></a><span class="lineno">  606</span>        <span class="keywordflow">return</span> *m_queue;</div>
<div class="line"><a id="l00607" name="l00607"></a><span class="lineno">  607</span>    }<span class="comment"></span></div>
<div class="line"><a id="l00608" name="l00608"></a><span class="lineno">  608</span><span class="comment">    ///\brief Returns the underlying storage structure for low level access</span></div>
<div class="line"><a id="l00609" name="l00609"></a><span class="lineno">  609</span><span class="comment"></span>    const_storage_type raw_storage()<span class="keyword"> const</span>{</div>
<div class="line"><a id="l00610" name="l00610"></a><span class="lineno">  610</span>        <span class="keywordflow">return</span> {m_storage.get_buffer(),0,leading_dimension()};</div>
<div class="line"><a id="l00611" name="l00611"></a><span class="lineno">  611</span>    }</div>
<div class="line"><a id="l00612" name="l00612"></a><span class="lineno">  612</span>    <span class="comment"></span></div>
<div class="line"><a id="l00613" name="l00613"></a><span class="lineno">  613</span><span class="comment">    ///\brief Returns the underlying storage structure for low level access</span></div>
<div class="line"><a id="l00614" name="l00614"></a><span class="lineno">  614</span><span class="comment"></span>    storage_type raw_storage(){</div>
<div class="line"><a id="l00615" name="l00615"></a><span class="lineno">  615</span>        <span class="keywordflow">return</span> {m_storage.get_buffer(),0,leading_dimension()};</div>
<div class="line"><a id="l00616" name="l00616"></a><span class="lineno">  616</span>    }</div>
<div class="line"><a id="l00617" name="l00617"></a><span class="lineno">  617</span>    </div>
<div class="line"><a id="l00618" name="l00618"></a><span class="lineno">  618</span>    <span class="comment"></span></div>
<div class="line"><a id="l00619" name="l00619"></a><span class="lineno">  619</span><span class="comment">    /// \brief Resize the matrix</span></div>
<div class="line"><a id="l00620" name="l00620"></a><span class="lineno">  620</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00621" name="l00621"></a><span class="lineno">  621</span><span class="comment">    /// This might erase all data stored in the matrix</span></div>
<div class="line"><a id="l00622" name="l00622"></a><span class="lineno">  622</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00623" name="l00623"></a><span class="lineno">  623</span><span class="comment">    /// \param size1 new number of rows</span></div>
<div class="line"><a id="l00624" name="l00624"></a><span class="lineno">  624</span><span class="comment">    /// \param size2 new number of columns</span></div>
<div class="line"><a id="l00625" name="l00625"></a><span class="lineno">  625</span><span class="comment"></span>    <span class="keywordtype">void</span> resize(size_type size1, size_type size2) {</div>
<div class="line"><a id="l00626" name="l00626"></a><span class="lineno">  626</span>        <span class="keywordflow">if</span>(size1 * size2 &lt; m_storage.size())</div>
<div class="line"><a id="l00627" name="l00627"></a><span class="lineno">  627</span>            m_storage.resize(size1 * size2);</div>
<div class="line"><a id="l00628" name="l00628"></a><span class="lineno">  628</span>        <span class="keywordflow">else</span></div>
<div class="line"><a id="l00629" name="l00629"></a><span class="lineno">  629</span>            m_storage = boost::compute::vector&lt;T&gt;(size1 * size2, queue().get_context());</div>
<div class="line"><a id="l00630" name="l00630"></a><span class="lineno">  630</span>        m_size1 = size1;</div>
<div class="line"><a id="l00631" name="l00631"></a><span class="lineno">  631</span>        m_size2 = size2;</div>
<div class="line"><a id="l00632" name="l00632"></a><span class="lineno">  632</span>    }</div>
<div class="line"><a id="l00633" name="l00633"></a><span class="lineno">  633</span> </div>
<div class="line"><a id="l00634" name="l00634"></a><span class="lineno">  634</span>    <span class="comment"></span></div>
<div class="line"><a id="l00635" name="l00635"></a><span class="lineno">  635</span><span class="comment">    /// \brief Resize the matrix</span></div>
<div class="line"><a id="l00636" name="l00636"></a><span class="lineno">  636</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00637" name="l00637"></a><span class="lineno">  637</span><span class="comment">    /// This will erase all data stored in the matrix and reinitialize it with the supplied value of init</span></div>
<div class="line"><a id="l00638" name="l00638"></a><span class="lineno">  638</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00639" name="l00639"></a><span class="lineno">  639</span><span class="comment">    /// \param size1 new number of rows</span></div>
<div class="line"><a id="l00640" name="l00640"></a><span class="lineno">  640</span><span class="comment">    /// \param size2 new number of columns</span></div>
<div class="line"><a id="l00641" name="l00641"></a><span class="lineno">  641</span><span class="comment">    /// \param init the value of all elements</span></div>
<div class="line"><a id="l00642" name="l00642"></a><span class="lineno">  642</span><span class="comment"></span>    <span class="keywordtype">void</span> resize(size_type size1, size_type size2, value_type init) {</div>
<div class="line"><a id="l00643" name="l00643"></a><span class="lineno">  643</span>        resize(size1,size2);</div>
<div class="line"><a id="l00644" name="l00644"></a><span class="lineno">  644</span>        boost::compute::fill(m_storage.begin(),m_storage.end(), init, queue());</div>
<div class="line"><a id="l00645" name="l00645"></a><span class="lineno">  645</span>    }</div>
<div class="line"><a id="l00646" name="l00646"></a><span class="lineno">  646</span>    </div>
<div class="line"><a id="l00647" name="l00647"></a><span class="lineno">  647</span>    <span class="keywordtype">void</span> clear(){</div>
<div class="line"><a id="l00648" name="l00648"></a><span class="lineno">  648</span>        boost::compute::fill(m_storage.begin(),m_storage.end(), value_type<span class="comment">/*zero*/</span>(), queue());</div>
<div class="line"><a id="l00649" name="l00649"></a><span class="lineno">  649</span>    }</div>
<div class="line"><a id="l00650" name="l00650"></a><span class="lineno">  650</span>    </div>
<div class="line"><a id="l00651" name="l00651"></a><span class="lineno">  651</span>    <span class="comment">// Iterator types</span></div>
<div class="line"><a id="l00652" name="l00652"></a><span class="lineno">  652</span>    <span class="keyword">typedef</span> no_iterator major_iterator;</div>
<div class="line"><a id="l00653" name="l00653"></a><span class="lineno">  653</span>    <span class="keyword">typedef</span> no_iterator const_major_iterator;</div>
<div class="line"><a id="l00654" name="l00654"></a><span class="lineno">  654</span><span class="comment"></span> </div>
<div class="line"><a id="l00655" name="l00655"></a><span class="lineno">  655</span><span class="comment">    /// \brief Swap the content of two matrixs</span></div>
<div class="line"><a id="l00656" name="l00656"></a><span class="lineno">  656</span><span class="comment">    /// \param m1 is the first matrix. It takes values from m2</span></div>
<div class="line"><a id="l00657" name="l00657"></a><span class="lineno">  657</span><span class="comment">    /// \param m2 is the second matrix It takes values from m1</span></div>
<div class="line"><a id="l00658" name="l00658"></a><span class="lineno">  658</span><span class="comment"></span>    <span class="keyword">friend</span> <span class="keywordtype">void</span> <a class="code hl_function" href="namespaceshark.html#a3fffe112e8e09ea8f41e4fb7113e93ee" title="Swaps the contents of two instances of KeyValuePair.">swap</a>(matrix&amp; m1, matrix&amp; m2) {</div>
<div class="line"><a id="l00659" name="l00659"></a><span class="lineno">  659</span>        <span class="keyword">using </span>std::swap;</div>
<div class="line"><a id="l00660" name="l00660"></a><span class="lineno">  660</span>        <a class="code hl_function" href="namespaceshark.html#a3fffe112e8e09ea8f41e4fb7113e93ee" title="Swaps the contents of two instances of KeyValuePair.">swap</a>(m1.m_storage,m2.m_storage);</div>
<div class="line"><a id="l00661" name="l00661"></a><span class="lineno">  661</span>        std::swap(m1.m_queue,m2.m_queue);</div>
<div class="line"><a id="l00662" name="l00662"></a><span class="lineno">  662</span>        std::swap(m1.m_size1,m2.m_size1);</div>
<div class="line"><a id="l00663" name="l00663"></a><span class="lineno">  663</span>        std::swap(m1.m_size2,m2.m_size2);</div>
<div class="line"><a id="l00664" name="l00664"></a><span class="lineno">  664</span>    }</div>
<div class="line"><a id="l00665" name="l00665"></a><span class="lineno">  665</span>    </div>
<div class="line"><a id="l00666" name="l00666"></a><span class="lineno">  666</span>    <span class="keyword">template</span>&lt;<span class="keyword">class</span> Archive&gt;</div>
<div class="line"><a id="l00667" name="l00667"></a><span class="lineno">  667</span>    <span class="keywordtype">void</span> serialize(Archive &amp;ar, <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> file_version) {</div>
<div class="line"><a id="l00668" name="l00668"></a><span class="lineno">  668</span>    }</div>
<div class="line"><a id="l00669" name="l00669"></a><span class="lineno">  669</span><span class="keyword">private</span>:</div>
<div class="line"><a id="l00670" name="l00670"></a><span class="lineno">  670</span>    std::size_t leading_dimension()<span class="keyword"> const</span>{</div>
<div class="line"><a id="l00671" name="l00671"></a><span class="lineno">  671</span>        <span class="keywordflow">return</span> orientation::index_m(m_size1, m_size2);</div>
<div class="line"><a id="l00672" name="l00672"></a><span class="lineno">  672</span>    };</div>
<div class="line"><a id="l00673" name="l00673"></a><span class="lineno">  673</span>    </div>
<div class="line"><a id="l00674" name="l00674"></a><span class="lineno">  674</span>    boost::compute::vector&lt;T&gt; m_storage;</div>
<div class="line"><a id="l00675" name="l00675"></a><span class="lineno">  675</span>    boost::compute::command_queue* m_queue;</div>
<div class="line"><a id="l00676" name="l00676"></a><span class="lineno">  676</span>    size_type m_size1;</div>
<div class="line"><a id="l00677" name="l00677"></a><span class="lineno">  677</span>    size_type m_size2;</div>
<div class="line"><a id="l00678" name="l00678"></a><span class="lineno">  678</span>};</div>
<div class="line"><a id="l00679" name="l00679"></a><span class="lineno">  679</span> </div>
<div class="line"><a id="l00680" name="l00680"></a><span class="lineno">  680</span> </div>
<div class="line"><a id="l00681" name="l00681"></a><span class="lineno">  681</span><span class="keyword">template</span>&lt;<span class="keyword">class</span> T, <span class="keyword">class</span> Orientation, <span class="keywordtype">bool</span> Upper, <span class="keywordtype">bool</span> Unit&gt;</div>
<div class="line"><a id="l00682" name="l00682"></a><span class="lineno">  682</span><span class="keyword">class </span>dense_triangular_proxy&lt;T, Orientation, triangular_tag&lt;Upper, Unit&gt; , gpu_tag&gt;</div>
<div class="line"><a id="l00683" name="l00683"></a><span class="lineno">  683</span>: <span class="keyword">public</span> matrix_expression&lt;dense_triangular_proxy&lt;T, Orientation, triangular_tag&lt;Upper, Unit&gt;, gpu_tag&gt;, gpu_tag&gt; {</div>
<div class="line"><a id="l00684" name="l00684"></a><span class="lineno">  684</span><span class="keyword">public</span>:</div>
<div class="line"><a id="l00685" name="l00685"></a><span class="lineno">  685</span>    <span class="keyword">typedef</span> std::size_t size_type;</div>
<div class="line"><a id="l00686" name="l00686"></a><span class="lineno">  686</span>    <span class="keyword">typedef</span> <span class="keyword">typename</span> std::remove_const&lt;T&gt;::type value_type;</div>
<div class="line"><a id="l00687" name="l00687"></a><span class="lineno">  687</span>    <span class="keyword">typedef</span> value_type result_type;</div>
<div class="line"><a id="l00688" name="l00688"></a><span class="lineno">  688</span>    <span class="keyword">typedef</span> <span class="keyword">typename</span> std::conditional&lt;Unit, value_type const&amp;, T&amp;&gt;::type reference;</div>
<div class="line"><a id="l00689" name="l00689"></a><span class="lineno">  689</span>    <span class="keyword">typedef</span> value_type <span class="keyword">const</span>&amp; const_reference;</div>
<div class="line"><a id="l00690" name="l00690"></a><span class="lineno">  690</span>    <span class="keyword">typedef</span> dense_triangular_proxy&lt;value_type const, Orientation, triangular_tag&lt;Upper, Unit&gt; , gpu_tag&gt; const_closure_type;</div>
<div class="line"><a id="l00691" name="l00691"></a><span class="lineno">  691</span>    <span class="keyword">typedef</span> dense_triangular_proxy&lt;T, Orientation, triangular_tag&lt;Upper, Unit&gt; , gpu_tag&gt; closure_type;</div>
<div class="line"><a id="l00692" name="l00692"></a><span class="lineno">  692</span> </div>
<div class="line"><a id="l00693" name="l00693"></a><span class="lineno">  693</span>    <span class="keyword">typedef</span> gpu::dense_matrix_storage&lt;T, dense_tag&gt; storage_type;</div>
<div class="line"><a id="l00694" name="l00694"></a><span class="lineno">  694</span>    <span class="keyword">typedef</span> gpu::dense_matrix_storage&lt;value_type const, dense_tag&gt; const_storage_type;</div>
<div class="line"><a id="l00695" name="l00695"></a><span class="lineno">  695</span> </div>
<div class="line"><a id="l00696" name="l00696"></a><span class="lineno">  696</span>    <span class="keyword">typedef</span> elementwise&lt;dense_tag&gt; evaluation_category;</div>
<div class="line"><a id="l00697" name="l00697"></a><span class="lineno">  697</span>    <span class="keyword">typedef</span> triangular&lt;Orientation,triangular_tag&lt;Upper, Unit&gt; &gt; orientation;</div>
<div class="line"><a id="l00698" name="l00698"></a><span class="lineno">  698</span> </div>
<div class="line"><a id="l00699" name="l00699"></a><span class="lineno">  699</span> </div>
<div class="line"><a id="l00700" name="l00700"></a><span class="lineno">  700</span>    <span class="keyword">template</span>&lt;<span class="keyword">class</span> U&gt;</div>
<div class="line"><a id="l00701" name="l00701"></a><span class="lineno">  701</span>    dense_triangular_proxy(dense_triangular_proxy&lt;U, Orientation, triangular_tag&lt;Upper, Unit&gt;, gpu_tag&gt; <span class="keyword">const</span>&amp; expression)</div>
<div class="line"><a id="l00702" name="l00702"></a><span class="lineno">  702</span>    : m_storage(expression.raw_storage())</div>
<div class="line"><a id="l00703" name="l00703"></a><span class="lineno">  703</span>    , m_queue(&amp;expression.queue())</div>
<div class="line"><a id="l00704" name="l00704"></a><span class="lineno">  704</span>    , m_size1(expression.size1())</div>
<div class="line"><a id="l00705" name="l00705"></a><span class="lineno">  705</span>    , m_size2(expression.size2()){}</div>
<div class="line"><a id="l00706" name="l00706"></a><span class="lineno">  706</span> </div>
<div class="line"><a id="l00707" name="l00707"></a><span class="lineno">  707</span>    dense_triangular_proxy(storage_type <span class="keyword">const</span>&amp; storage, boost::compute::command_queue&amp; queue, std::size_t size1, std::size_t size2)</div>
<div class="line"><a id="l00708" name="l00708"></a><span class="lineno">  708</span>    : m_storage(storage)</div>
<div class="line"><a id="l00709" name="l00709"></a><span class="lineno">  709</span>    , m_queue(&amp;queue)</div>
<div class="line"><a id="l00710" name="l00710"></a><span class="lineno">  710</span>    , m_size1(size1)</div>
<div class="line"><a id="l00711" name="l00711"></a><span class="lineno">  711</span>    , m_size2(size2){}</div>
<div class="line"><a id="l00712" name="l00712"></a><span class="lineno">  712</span>    </div>
<div class="line"><a id="l00713" name="l00713"></a><span class="lineno">  713</span>    dense_matrix_adaptor&lt;T, Orientation, dense_tag, gpu_tag&gt; to_dense()<span class="keyword"> const</span>{</div>
<div class="line"><a id="l00714" name="l00714"></a><span class="lineno">  714</span>        <span class="keywordflow">return</span> {m_storage, queue(), m_size1, m_size2};</div>
<div class="line"><a id="l00715" name="l00715"></a><span class="lineno">  715</span>    }</div>
<div class="line"><a id="l00716" name="l00716"></a><span class="lineno">  716</span>    </div>
<div class="line"><a id="l00717" name="l00717"></a><span class="lineno">  717</span>    <span class="comment"></span></div>
<div class="line"><a id="l00718" name="l00718"></a><span class="lineno">  718</span><span class="comment">    /// \brief Return the number of rows of the matrix</span></div>
<div class="line"><a id="l00719" name="l00719"></a><span class="lineno">  719</span><span class="comment"></span>    size_type size1()<span class="keyword"> const </span>{</div>
<div class="line"><a id="l00720" name="l00720"></a><span class="lineno">  720</span>        <span class="keywordflow">return</span> m_size1;</div>
<div class="line"><a id="l00721" name="l00721"></a><span class="lineno">  721</span>    }<span class="comment"></span></div>
<div class="line"><a id="l00722" name="l00722"></a><span class="lineno">  722</span><span class="comment">    /// \brief Return the number of columns of the matrix</span></div>
<div class="line"><a id="l00723" name="l00723"></a><span class="lineno">  723</span><span class="comment"></span>    size_type size2()<span class="keyword"> const </span>{</div>
<div class="line"><a id="l00724" name="l00724"></a><span class="lineno">  724</span>        <span class="keywordflow">return</span> m_size2;</div>
<div class="line"><a id="l00725" name="l00725"></a><span class="lineno">  725</span>    }</div>
<div class="line"><a id="l00726" name="l00726"></a><span class="lineno">  726</span>    <span class="comment"></span></div>
<div class="line"><a id="l00727" name="l00727"></a><span class="lineno">  727</span><span class="comment">    ///\brief Returns the underlying storage structure for low level access</span></div>
<div class="line"><a id="l00728" name="l00728"></a><span class="lineno">  728</span><span class="comment"></span>    storage_type raw_storage()<span class="keyword"> const</span>{</div>
<div class="line"><a id="l00729" name="l00729"></a><span class="lineno">  729</span>        <span class="keywordflow">return</span> m_storage;</div>
<div class="line"><a id="l00730" name="l00730"></a><span class="lineno">  730</span>    }</div>
<div class="line"><a id="l00731" name="l00731"></a><span class="lineno">  731</span>    </div>
<div class="line"><a id="l00732" name="l00732"></a><span class="lineno">  732</span>     boost::compute::command_queue&amp; queue()<span class="keyword">const</span>{</div>
<div class="line"><a id="l00733" name="l00733"></a><span class="lineno">  733</span>        <span class="keywordflow">return</span> *m_queue;</div>
<div class="line"><a id="l00734" name="l00734"></a><span class="lineno">  734</span>    }</div>
<div class="line"><a id="l00735" name="l00735"></a><span class="lineno">  735</span> </div>
<div class="line"><a id="l00736" name="l00736"></a><span class="lineno">  736</span>    <span class="keyword">typedef</span> no_iterator major_iterator;</div>
<div class="line"><a id="l00737" name="l00737"></a><span class="lineno">  737</span>    <span class="keyword">typedef</span> no_iterator const_major_iterator;</div>
<div class="line"><a id="l00738" name="l00738"></a><span class="lineno">  738</span><span class="keyword">private</span>:</div>
<div class="line"><a id="l00739" name="l00739"></a><span class="lineno">  739</span>    storage_type m_storage;</div>
<div class="line"><a id="l00740" name="l00740"></a><span class="lineno">  740</span>    boost::compute::command_queue* m_queue;</div>
<div class="line"><a id="l00741" name="l00741"></a><span class="lineno">  741</span>    std::size_t m_size1;</div>
<div class="line"><a id="l00742" name="l00742"></a><span class="lineno">  742</span>    std::size_t m_size2;</div>
<div class="line"><a id="l00743" name="l00743"></a><span class="lineno">  743</span>};</div>
<div class="line"><a id="l00744" name="l00744"></a><span class="lineno">  744</span><span class="comment"></span> </div>
<div class="line"><a id="l00745" name="l00745"></a><span class="lineno">  745</span><span class="comment">//////////////////////////////////</span></div>
<div class="line"><a id="l00746" name="l00746"></a><span class="lineno">  746</span><span class="comment">//////Expression Traits</span></div>
<div class="line"><a id="l00747" name="l00747"></a><span class="lineno">  747</span><span class="comment">///////////////////////////////////</span></div>
<div class="line"><a id="l00748" name="l00748"></a><span class="lineno">  748</span><span class="comment"></span> </div>
<div class="line"><a id="l00749" name="l00749"></a><span class="lineno">  749</span><span class="keyword">template</span>&lt;<span class="keyword">class</span> T&gt;</div>
<div class="line"><a id="l00750" name="l00750"></a><span class="lineno">  750</span><span class="keyword">struct </span>ExpressionToFunctor&lt;vector&lt;T, gpu_tag&gt; &gt;{</div>
<div class="line"><a id="l00751" name="l00751"></a><span class="lineno">  751</span>    <span class="keyword">static</span> gpu::detail::dense_vector_element&lt;T&gt; <a class="code hl_function" href="group__shark__globals.html#gab87e0d38b9fbf74d9a97ee02e8ab273b" title="Transforms a dataset using a Functor f and returns the transformed result.">transform</a>(vector&lt;T, gpu_tag&gt; <span class="keyword">const</span>&amp; e){</div>
<div class="line"><a id="l00752" name="l00752"></a><span class="lineno">  752</span>        <span class="keywordflow">return</span> {e().raw_storage().buffer, 1, 0}; </div>
<div class="line"><a id="l00753" name="l00753"></a><span class="lineno">  753</span>    }</div>
<div class="line"><a id="l00754" name="l00754"></a><span class="lineno">  754</span>};</div>
<div class="line"><a id="l00755" name="l00755"></a><span class="lineno">  755</span> </div>
<div class="line"><a id="l00756" name="l00756"></a><span class="lineno">  756</span><span class="keyword">template</span>&lt;<span class="keyword">class</span> T, <span class="keyword">class</span> Orientation&gt;</div>
<div class="line"><a id="l00757" name="l00757"></a><span class="lineno">  757</span><span class="keyword">struct </span>ExpressionToFunctor&lt;matrix&lt;T, Orientation, gpu_tag&gt; &gt;{</div>
<div class="line"><a id="l00758" name="l00758"></a><span class="lineno">  758</span>    <span class="keyword">static</span> gpu::detail::dense_matrix_element&lt;T&gt; <a class="code hl_function" href="group__shark__globals.html#gab87e0d38b9fbf74d9a97ee02e8ab273b" title="Transforms a dataset using a Functor f and returns the transformed result.">transform</a>(matrix&lt;T, Orientation, gpu_tag&gt; <span class="keyword">const</span>&amp; e){</div>
<div class="line"><a id="l00759" name="l00759"></a><span class="lineno">  759</span>        std::size_t leading = e().raw_storage().leading_dimension;</div>
<div class="line"><a id="l00760" name="l00760"></a><span class="lineno">  760</span>        <span class="keywordflow">return</span> {e().raw_storage().buffer, Orientation::stride1(leading), Orientation::stride2(leading),0}; </div>
<div class="line"><a id="l00761" name="l00761"></a><span class="lineno">  761</span>    }</div>
<div class="line"><a id="l00762" name="l00762"></a><span class="lineno">  762</span>};</div>
<div class="line"><a id="l00763" name="l00763"></a><span class="lineno">  763</span> </div>
<div class="line"><a id="l00764" name="l00764"></a><span class="lineno">  764</span> </div>
<div class="line"><a id="l00765" name="l00765"></a><span class="lineno">  765</span> </div>
<div class="line"><a id="l00766" name="l00766"></a><span class="lineno">  766</span><span class="keyword">template</span>&lt;<span class="keyword">class</span> T, <span class="keyword">class</span> Tag&gt;</div>
<div class="line"><a id="l00767" name="l00767"></a><span class="lineno">  767</span><span class="keyword">struct </span>ExpressionToFunctor&lt;dense_vector_adaptor&lt;T, Tag, gpu_tag&gt; &gt;{</div>
<div class="line"><a id="l00768" name="l00768"></a><span class="lineno">  768</span>    <span class="keyword">static</span> gpu::detail::dense_vector_element&lt;T&gt; <a class="code hl_function" href="group__shark__globals.html#gab87e0d38b9fbf74d9a97ee02e8ab273b" title="Transforms a dataset using a Functor f and returns the transformed result.">transform</a>(dense_vector_adaptor&lt;T, Tag, gpu_tag&gt; <span class="keyword">const</span>&amp; e){</div>
<div class="line"><a id="l00769" name="l00769"></a><span class="lineno">  769</span>        <span class="keyword">auto</span> <span class="keyword">const</span>&amp; storage = e().raw_storage(); </div>
<div class="line"><a id="l00770" name="l00770"></a><span class="lineno">  770</span>        <span class="keywordflow">return</span> {storage.buffer, storage.stride, storage.offset}; </div>
<div class="line"><a id="l00771" name="l00771"></a><span class="lineno">  771</span>    }</div>
<div class="line"><a id="l00772" name="l00772"></a><span class="lineno">  772</span>};</div>
<div class="line"><a id="l00773" name="l00773"></a><span class="lineno">  773</span> </div>
<div class="line"><a id="l00774" name="l00774"></a><span class="lineno">  774</span><span class="keyword">template</span>&lt;<span class="keyword">class</span> T, <span class="keyword">class</span> Tag, <span class="keyword">class</span> Orientation&gt;</div>
<div class="line"><a id="l00775" name="l00775"></a><span class="lineno">  775</span><span class="keyword">struct </span>ExpressionToFunctor&lt;dense_matrix_adaptor&lt;T, Orientation, Tag, gpu_tag&gt; &gt;{</div>
<div class="line"><a id="l00776" name="l00776"></a><span class="lineno">  776</span>    <span class="keyword">static</span> gpu::detail::dense_matrix_element&lt;T&gt; <a class="code hl_function" href="group__shark__globals.html#gab87e0d38b9fbf74d9a97ee02e8ab273b" title="Transforms a dataset using a Functor f and returns the transformed result.">transform</a>(dense_matrix_adaptor&lt;T, Orientation, Tag, gpu_tag&gt; <span class="keyword">const</span>&amp; e){</div>
<div class="line"><a id="l00777" name="l00777"></a><span class="lineno">  777</span>        <span class="keyword">auto</span> <span class="keyword">const</span>&amp; storage = e().raw_storage(); </div>
<div class="line"><a id="l00778" name="l00778"></a><span class="lineno">  778</span>        std::size_t stride1 = Orientation::index_m(std::size_t(1), storage.leading_dimension);</div>
<div class="line"><a id="l00779" name="l00779"></a><span class="lineno">  779</span>        std::size_t stride2 = Orientation::index_M(std::size_t(1), storage.leading_dimension);</div>
<div class="line"><a id="l00780" name="l00780"></a><span class="lineno">  780</span>        <span class="keywordflow">return</span> {storage.buffer, stride1, stride2, storage.offset}; </div>
<div class="line"><a id="l00781" name="l00781"></a><span class="lineno">  781</span>    }</div>
<div class="line"><a id="l00782" name="l00782"></a><span class="lineno">  782</span>};</div>
<div class="line"><a id="l00783" name="l00783"></a><span class="lineno">  783</span> </div>
<div class="line"><a id="l00784" name="l00784"></a><span class="lineno">  784</span><span class="keyword">namespace </span>detail{</div>
<div class="line"><a id="l00785" name="l00785"></a><span class="lineno">  785</span> </div>
<div class="line"><a id="l00786" name="l00786"></a><span class="lineno">  786</span><span class="keyword">template</span>&lt;<span class="keyword">class</span> T, <span class="keyword">class</span> Orientation&gt;</div>
<div class="line"><a id="l00787" name="l00787"></a><span class="lineno">  787</span><span class="keyword">struct </span>vector_to_matrix_optimizer&lt;dense_vector_adaptor&lt;T, continuous_dense_tag, gpu_tag&gt;, Orientation &gt;{</div>
<div class="line"><a id="l00788" name="l00788"></a><span class="lineno">  788</span>    <span class="keyword">typedef</span> dense_matrix_adaptor&lt;T, Orientation, continuous_dense_tag, gpu_tag&gt; type;</div>
<div class="line"><a id="l00789" name="l00789"></a><span class="lineno">  789</span>    </div>
<div class="line"><a id="l00790" name="l00790"></a><span class="lineno">  790</span>    <span class="keyword">static</span> type create(</div>
<div class="line"><a id="l00791" name="l00791"></a><span class="lineno">  791</span>        dense_vector_adaptor&lt;T, continuous_dense_tag, gpu_tag&gt; <span class="keyword">const</span>&amp; v,</div>
<div class="line"><a id="l00792" name="l00792"></a><span class="lineno">  792</span>        std::size_t size1, std::size_t size2</div>
<div class="line"><a id="l00793" name="l00793"></a><span class="lineno">  793</span>    ){</div>
<div class="line"><a id="l00794" name="l00794"></a><span class="lineno">  794</span>        gpu::dense_matrix_storage&lt;T, continuous_dense_tag&gt; storage = {v.raw_storage().buffer, v.raw_storage().offset, Orientation::index_m(size1,size2)};</div>
<div class="line"><a id="l00795" name="l00795"></a><span class="lineno">  795</span>        <span class="keywordflow">return</span> type(storage, v.queue(), size1, size2);</div>
<div class="line"><a id="l00796" name="l00796"></a><span class="lineno">  796</span>    }</div>
<div class="line"><a id="l00797" name="l00797"></a><span class="lineno">  797</span>};</div>
<div class="line"><a id="l00798" name="l00798"></a><span class="lineno">  798</span>}</div>
<div class="line"><a id="l00799" name="l00799"></a><span class="lineno">  799</span> </div>
<div class="line"><a id="l00800" name="l00800"></a><span class="lineno">  800</span>}</div>
<div class="line"><a id="l00801" name="l00801"></a><span class="lineno">  801</span> </div>
<div class="line"><a id="l00802" name="l00802"></a><span class="lineno">  802</span><span class="preprocessor">#endif</span></div>
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